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ORCIDDaniel E. Quevedo
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- affiliation: Sydney University, Australia
- affiliation (former): Queensland University of Technology, School of Electrical Engineering and Robotics, Brisbane, Australia
- affiliation (former): Universität Paderborn
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2020 – today
- 2025
[j122]Matthew Crimson, Justin M. Kennedy, Daniel E. Quevedo:
Remote state estimation with privacy against active eavesdroppers. Autom. 171: 111932 (2025)- 2024
- [j121]Wanchun Liu, Alex S. Leong, Daniel E. Quevedo
:
Thompson sampling for networked control over unknown channels. Autom. 165: 111684 (2024) - [j120]Zihuai Zhao, Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Branka Vucetic:
Deep Learning for Wireless-Networked Systems: A Joint Estimation-Control-Scheduling Approach. IEEE Internet Things J. 11(3): 4535-4550 (2024) - [j119]Yake Yang, Yuzhe Li, Yang Shi, Daniel E. Quevedo:
The Vulnerability Analysis of Remote Estimation With Batch-Data Detectors Against Integrity Attacks. IEEE Trans. Autom. Control. 69(5): 3096-3111 (2024) - [j118]Justin M. Kennedy, Jason J. Ford, Daniel E. Quevedo, Falko Dressler:
Innovation-Based Remote State Estimation Secrecy With No Acknowledgments. IEEE Trans. Autom. Control. 69(11): 7433-7448 (2024) - [j117]Fuyi Qu, Nachuan Yang, Hao Liu, Yuzhe Li, Daniel E. Quevedo:
Time-Stamp Attacks on Remote State Estimation in Cyber-Physical Systems. IEEE Trans. Control. Netw. Syst. 11(1): 450-461 (2024) - [j116]Jiazheng Chen, Wanchun Liu, Daniel E. Quevedo, Saeed R. Khosravirad, Yonghui Li, Branka Vucetic:
Structure-Enhanced DRL for Optimal Transmission Scheduling. IEEE Trans. Wirel. Commun. 23(1): 379-393 (2024) - [c74]Manuel Klädtke, Moritz Schulze Darup, Daniel E. Quevedo:
Extending Direct Data-Driven Predictive Control Towards Systems with Finite Control Sets. ECC 2024: 3345-3350 - [i64]Xinhao Yan, Guanzhong Zhou, Daniel E. Quevedo, Carlos Murguia, Bo Chen, Hailong Huang:
Privacy-Preserving State Estimation in the Presence of Eavesdroppers: A Survey. CoRR abs/2402.15738 (2024) - [i63]Manuel Klädtke, Moritz Schulze Darup, Daniel E. Quevedo:
Extending direct data-driven predictive control towards systems with finite control sets. CoRR abs/2404.02727 (2024) - [i62]Gaoyang Pang, Wanchun Liu, Dusit Niyato, Daniel E. Quevedo, Branka Vucetic, Yonghui Li:
Wireless Human-Machine Collaboration in Industry 5.0. CoRR abs/2410.14153 (2024) - 2023
- [j115]Masaaki Nagahara, Kai Cai, Debasish Chatterjee, Nikhil Chopra, Takeshi Hatanaka, Yutaka Hori, Hideaki Ishii, Daniel E. Quevedo, Michel A. Reniers:
Special issue on control technology for networked and distributed robotics. Adv. Robotics 37(1-2): 1 (2023) - [j114]Masaaki Nagahara, Kai Cai, Debasish Chatterjee, Nikhil Chopra, Takeshi Hatanaka, Yutaka Hori, Hideaki Ishii, Daniel E. Quevedo, Michel A. Reniers:
Special issue on control technology for networked and distributed robotics (Part II). Adv. Robotics 37(3): 155 (2023) - [j113]Jingyi Lu, Daniel E. Quevedo:
A jointly optimal design of control and scheduling in networked systems under denial-of-service attacks. Autom. 148: 110774 (2023) - [j112]Yong Xu, Haoxiang Xiang, Lixin Yang, Renquan Lu, Daniel E. Quevedo:
Optimal transmission strategy for multiple Markovian fading channels: Existence, structure, and approximation. Autom. 158: 111312 (2023) - [j111]Robert C. Ballam, Aaron McFadyen, Daniel E. Quevedo:
Local Averaging for Consensus Over Communication Links With Random Dropouts. IEEE Control. Syst. Lett. 7: 1387-1392 (2023) - [j110]Vineeth S. Varma, Romain Postoyan, Daniel E. Quevedo, Irinel-Constantin Morarescu:
Event-Triggered Transmission Policies for Nonlinear Control Systems Over Erasure Channels. IEEE Control. Syst. Lett. 7: 2113-2118 (2023) - [j109]Jiazheng Chen, Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Branka Vucetic:
Semantic-Aware Transmission Scheduling: A Monotonicity-Driven Deep Reinforcement Learning Approach. IEEE Commun. Lett. 27(12): 3260-3264 (2023) - [j108]Jingyi Lu, Daniel E. Quevedo, Vijay Gupta, Subhrakanti Dey:
Stealthy Hacking and Secrecy of Controlled State Estimation Systems With Random Dropouts. IEEE Trans. Autom. Control. 68(1): 31-46 (2023) - [j107]Vineeth Satheeskumar Varma, Romain Postoyan, Daniel E. Quevedo, Irinel-Constantin Morarescu:
Transmission Power Policies for Energy-Efficient Wireless Control of Nonlinear Systems. IEEE Trans. Autom. Control. 68(6): 3362-3376 (2023) - [j106]Yuzhe Li, Yake Yang, Zhengen Zhao, Jing Zhou, Daniel E. Quevedo:
Deception Attacks on Remote Estimation With Disclosure and Disruption Resources. IEEE Trans. Autom. Control. 68(7): 4096-4112 (2023) - [j105]Wanchun Liu, Daniel E. Quevedo, Karl Henrik Johansson, Branka Vucetic, Yonghui Li:
Stability Conditions for Remote State Estimation of Multiple Systems Over Multiple Markov Fading Channels. IEEE Trans. Autom. Control. 68(7): 4273-4280 (2023) - [j104]Alex S. Leong, Daniel E. Quevedo, Wanchun Liu:
Stability Enforced Bandit Algorithms for Channel Selection in Remote State Estimation of Gauss-Markov Processes. IEEE Trans. Autom. Control. 68(12): 8308-8315 (2023) - [j103]Yang Li, D. Mahinda Vilathgamuwa, Daniel E. Quevedo, Chih Feng Lee, Changfu Zou:
Ensemble Nonlinear Model Predictive Control for Residential Solar Battery Energy Management. IEEE Trans. Control. Syst. Technol. 31(5): 2188-2200 (2023) - [j102]Lixin Yang, Yong Xu, Zenghong Huang, Hong-Xia Rao, Daniel E. Quevedo:
Learning Optimal Stochastic Sensor Scheduling for Remote Estimation With Channel Capacity Constraint. IEEE Trans. Ind. Informatics 19(3): 2565-2573 (2023) - [j101]Justin M. Kennedy, Julian Heinovski, Daniel E. Quevedo, Falko Dressler:
Centralized Model Predictive Control With Human-Driver Interaction for Platooning. IEEE Trans. Veh. Technol. 72(10): 12664-12680 (2023) - [c73]Jiazheng Chen, Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Branka Vucetic:
Structure-Enhanced Deep Reinforcement Learning for Optimal Transmission Scheduling. ICC 2023: 1212-1218 - [i61]Yang Li, D. Mahinda Vilathgamuwa, Daniel E. Quevedo, Chih Feng Lee, Changfu Zou:
Ensemble Nonlinear Model Predictive Control for Residential Solar-Battery Energy Management. CoRR abs/2303.10393 (2023) - [i60]Jiazheng Chen, Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Branka Vucetic:
Semantic-aware Transmission Scheduling: a Monotonicity-driven Deep Reinforcement Learning Approach. CoRR abs/2305.13706 (2023) - [i59]Matthew Crimson, Justin M. Kennedy, Daniel E. Quevedo:
Remote State Estimation with Privacy Against Active Eavesdroppers. CoRR abs/2308.08790 (2023) - 2022
- [j100]Yong Xu, Weijun Lv, Weiqun Lin, Renquan Lu, Daniel E. Quevedo:
On extended state estimation for nonlinear uncertain systems with round-robin protocol. Autom. 138: 110154 (2022) - [j99]Zahra Jadidi, Joshua Hagemann, Daniel E. Quevedo:
Multi-step attack detection in industrial control systems using causal analysis. Comput. Ind. 142: 103741 (2022) - [j98]Wanchun Liu, Daniel E. Quevedo, Branka Vucetic, Yonghui Li:
Stability Conditions for Remote State Estimation of Multiple Systems Over Semi-Markov Fading Channels. IEEE Control. Syst. Lett. 6: 2954-2959 (2022) - [j97]Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Karl Henrik Johansson, Branka Vucetic:
Remote State Estimation With Smart Sensors Over Markov Fading Channels. IEEE Trans. Autom. Control. 67(6): 2743-2757 (2022) - [j96]Arunselvan Ramaswamy, Adrian Redder, Daniel E. Quevedo:
Optimization Over Time-Varying Networks and Unbounded Information Delays. IEEE Trans. Autom. Control. 67(8): 4131-4137 (2022) - [j95]Marvin Lücke, Jingyi Lu, Daniel E. Quevedo:
Coding for Secrecy in Remote State Estimation With an Adversary. IEEE Trans. Autom. Control. 67(9): 4955-4962 (2022) - [j94]Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Branka Vucetic:
Anytime Control Under Practical Communication Models. IEEE Trans. Autom. Control. 67(10): 5400-5407 (2022) - [j93]Moritz Schulze Darup, Gerrit Book, Daniel E. Quevedo, Masaaki Nagahara:
Fast Hands-Off Control Using ADMM Real-Time Iterations. IEEE Trans. Autom. Control. 67(10): 5416-5423 (2022) - [j92]Yue Zhao, Xin Du, Chunjie Zhou, Yu-Chu Tian, Xiaoya Hu, Daniel E. Quevedo:
Adaptive Resilient Control of Cyber-Physical Systems Under Actuator and Sensor Attacks. IEEE Trans. Ind. Informatics 18(5): 3203-3212 (2022) - [c72]Robert C. Ballam, Aaron McFadyen, Daniel E. Quevedo:
H2 Controller Design for Multi-Agent Systems with Markovian Switching Topologies. ANZCC 2022: 103-108 - [c71]Justin M. Kennedy, Jason J. Ford, Daniel E. Quevedo:
Bayesian Quickest Change Detection of an Intruder in Acknowledgments for Private Remote State Estimation. ANZCC 2022: 243-248 - [c70]Teresa Arauz, José María Maestre, Daniel E. Quevedo, Eduardo Fernández Camacho:
Tree-based Model Predictive Control Strategy for Software Rejuvenation. CDC 2022: 1124-1129 - [i58]Wanchun Liu, Daniel E. Quevedo, Branka Vucetic, Yonghui Li:
Remote State Estimation of Multiple Systems over Semi-Markov Wireless Fading Channels. CoRR abs/2203.16826 (2022) - [i57]Justin M. Kennedy, Julian Heinovski, Daniel E. Quevedo, Falko Dressler:
Centralized Model-Predictive Control with Human-Driver Interaction for Platooning. CoRR abs/2205.09259 (2022) - [i56]Alex S. Leong, Daniel E. Quevedo:
Stability Enforced Bandit Algorithms for Channel Selection in Remote State Estimation. CoRR abs/2205.09923 (2022) - [i55]Justin M. Kennedy, Jason J. Ford, Daniel E. Quevedo:
Bayesian Quickest Change Detection of an Intruder in Acknowledgments for Private Remote State Estimation. CoRR abs/2207.08329 (2022) - [i54]Zihuai Zhao, Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Branka Vucetic:
Deep Learning for Wireless Networked Systems: a joint Estimation-Control-Scheduling Approach. CoRR abs/2210.00673 (2022) - [i53]Jiazheng Chen, Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Branka Vucetic:
Structure-Enhanced Deep Reinforcement Learning for Optimal Transmission Scheduling. CoRR abs/2211.10827 (2022) - [i52]Matthew Crimson, Justin M. Kennedy, Daniel E. Quevedo:
Remote State Estimation with Privacy Against Eavesdroppers. CoRR abs/2211.13411 (2022) - [i51]Justin M. Kennedy, Jason J. Ford, Daniel E. Quevedo, Falko Dressler:
Innovation-Based Remote State Estimation Secrecy with no Acknowledgments. CoRR abs/2212.08234 (2022) - [i50]Jiazheng Chen, Wanchun Liu, Daniel E. Quevedo, Saeed R. Khosravirad, Yonghui Li, Branka Vucetic:
Structure-Enhanced DRL for Optimal Transmission Scheduling. CoRR abs/2212.12704 (2022) - 2021
- [j91]Lingying Huang, Kemi Ding, Alex S. Leong, Daniel E. Quevedo, Ling Shi:
Encryption scheduling for remote state estimation under an operation constraint. Autom. 127: 109537 (2021) - [j90]Kemi Ding, Xiaoqiang Ren, Alex S. Leong, Daniel E. Quevedo, Ling Shi:
Remote State Estimation in the Presence of an Active Eavesdropper. IEEE Trans. Autom. Control. 66(1): 229-244 (2021) - [j89]Arunselvan Ramaswamy, Shalabh Bhatnagar, Daniel E. Quevedo:
Asynchronous Stochastic Approximations With Asymptotically Biased Errors and Deep Multiagent Learning. IEEE Trans. Autom. Control. 66(9): 3969-3983 (2021) - [j88]Atreyee Kundu, Daniel E. Quevedo:
On Periodic Scheduling and Control for Networked Systems Under Random Data Loss. IEEE Trans. Control. Netw. Syst. 8(4): 1788-1798 (2021) - [j87]Mingjing Sun, Chengcheng Zhao, Jianping He, Peng Cheng, Daniel E. Quevedo:
Privacy-Preserving Correlated Data Publication: Privacy Analysis and Optimal Noise Design. IEEE Trans. Netw. Sci. Eng. 8(3): 2014-2024 (2021) - [i49]Jingyi Lu, Daniel E. Quevedo:
Co-design of Control and Scheduling in Networked Systems under Denial-of-Service attacks. CoRR abs/2103.05893 (2021) - [i48]Wanchun Liu, Daniel E. Quevedo, Karl Henrik Johansson, Branka Vucetic, Yonghui Li:
Remote State Estimation of Multiple Systems over Multiple Markov Fading Channels. CoRR abs/2104.04181 (2021) - [i47]Wanchun Liu, Kang Huang, Daniel E. Quevedo, Branka Vucetic, Yonghui Li:
Deep Reinforcement Learning for Wireless Scheduling in Distributed Networked Control. CoRR abs/2109.12562 (2021) - [i46]Vineeth S. Varma, Romain Postoyan, Daniel E. Quevedo, Irinel-Constantin Morarescu:
Transmission power policies for energy-efficient wireless control of nonlinear system. CoRR abs/2111.09474 (2021) - 2020
- [j86]Kemi Ding, Xiaoqiang Ren, Daniel E. Quevedo, Subhrakanti Dey, Ling Shi:
Defensive deception against reactive jamming attacks in remote state estimation. Autom. 113: 108680 (2020) - [j85]Alex S. Leong, Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl, Ling Shi:
Deep reinforcement learning for wireless sensor scheduling in cyber-physical systems. Autom. 113: 108759 (2020) - [j84]Prabhat Kumar Mishra, Debasish Chatterjee, Daniel E. Quevedo:
Stochastic predictive control under intermittent observations and unreliable actions. Autom. 118: 109012 (2020) - [j83]Atreyee Kundu, Daniel E. Quevedo:
Stabilizing Scheduling Policies for Networked Control Systems. IEEE Trans. Control. Netw. Syst. 7(1): 163-175 (2020) - [c69]Vineeth S. Varma, Romain Postoyan, Daniel E. Quevedo, Irinel-Constantin Morarescu:
Time-based transmission power policies for energy-efficient wireless control of nonlinear systems. CDC 2020: 1854-1859 - [c68]Yogesh Kumar, Sukumar Srikant, Masaaki Nagahara, Debasish Chatterjee, Daniel E. Quevedo:
Maximum hands-off feedback control for finite-time stabilization. CDC 2020: 3969-3974 - [c67]Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey:
A Game-Theoretic Approach to Covert Communications. PIMRC 2020: 1-6 - [i45]Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Karl Henrik Johansson, Branka Vucetic:
Remote State Estimation with Smart Sensors over Markov Fading Channels. CoRR abs/2005.07871 (2020) - [i44]Marius Protte, Rene Fahr, Daniel E. Quevedo:
Behavioral Economics for Human-in-the-loop Control Systems Design: Overconfidence and the hot hand fallacy. CoRR abs/2007.15869 (2020) - [i43]Moritz Schulze Darup, Andreea B. Alexandru, Daniel E. Quevedo, George J. Pappas:
Encrypted control for networked systems - An illustrative introduction and current challenges. CoRR abs/2010.00268 (2020) - [i42]Atreyee Kundu, Daniel E. Quevedo:
Design of periodic scheduling and control for networked systems under random data loss. CoRR abs/2010.08447 (2020) - [i41]Jingyi Lu, Daniel E. Quevedo, Vijay Gupta, Subhrakanti Dey:
Stealthy hacking and secrecy of controlled state estimation systems with random dropouts. CoRR abs/2011.03745 (2020) - [i40]Wanchun Liu, Daniel E. Quevedo, Yonghui Li, Branka Vucetic:
Anytime Control with Markovian Computation and Communication Resources. CoRR abs/2012.00962 (2020)
2010 – 2019
- 2019
- [j82]Knut Graichen, Daniel E. Quevedo:
Ausgewählte Beiträge des GMA-Fachausschusses 1.50. Autom. 67(12): 988-989 (2019) - [j81]Moritz Schulze Darup, Adrian Redder, Daniel E. Quevedo:
Encrypted Cooperative Control Based on Structured Feedback. IEEE Control. Syst. Lett. 3(1): 37-42 (2019) - [j80]Alex S. Leong, Daniel E. Quevedo, Daniel Dolz, Subhrakanti Dey:
Information Bounds for State Estimation in the Presence of an Eavesdropper. IEEE Control. Syst. Lett. 3(3): 547-552 (2019) - [j79]Thuy V. Dang, Keck Voon Ling, Daniel E. Quevedo:
Stability Analysis of Event-Triggered Anytime Control With Multiple Control Laws. IEEE Trans. Autom. Control. 64(1): 420-426 (2019) - [j78]Burak Demirel, Alex S. Leong, Vijay Gupta, Daniel E. Quevedo:
Tradeoffs in Stochastic Event-Triggered Control. IEEE Trans. Autom. Control. 64(6): 2567-2574 (2019) - [j77]Alex S. Leong, Daniel E. Quevedo, Daniel Dolz, Subhrakanti Dey:
Transmission Scheduling for Remote State Estimation Over Packet Dropping Links in the Presence of an Eavesdropper. IEEE Trans. Autom. Control. 64(9): 3732-3739 (2019) - [j76]Steffi Knorn, Subhrakanti Dey, Anders Ahlén, Daniel E. Quevedo:
Optimal Energy Allocation in Multisensor Estimation Over Wireless Channels Using Energy Harvesting and Sharing. IEEE Trans. Autom. Control. 64(10): 4337-4344 (2019) - [j75]Kemi Ding, Xiaoqiang Ren, Daniel E. Quevedo, Subhrakanti Dey, Ling Shi:
DoS Attacks on Remote State Estimation With Asymmetric Information. IEEE Trans. Control. Netw. Syst. 6(2): 653-666 (2019) - [j74]Yuqing Ni, Alex S. Leong, Daniel E. Quevedo, Ling Shi:
Pricing and Selection of Channels for Remote State Estimation Using a Stackelberg Game Framework. IEEE Trans. Signal Inf. Process. over Networks 5(4): 657-668 (2019) - [j73]Ziyang Guo, Dawei Shi, Daniel E. Quevedo, Ling Shi:
Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach. IEEE Trans. Signal Process. 67(1): 194-207 (2019) - [c66]Lingying Huang, Alex S. Leong, Daniel E. Quevedo, Ling Shi:
Finite Time Encryption Schedule in the Presence of an Eavesdropper with Operation Cost. ACC 2019: 4063-4068 - [c65]Navid Noroozi, Roxanne Jackson, Daniel E. Quevedo, Fabian R. Wirth, Rolf Findeisen:
On noise-to-state stability of stochastic discrete-time systems via finite-step Lyapunov functions. CDC 2019: 5406-5411 - [c64]Markus J. Kögel, Daniel E. Quevedo, Rolf Findeisen:
Combined control and communication scheduling for constrained system using robust output feedback MPC. ECC 2019: 1778-1783 - [i39]Atreyee Kundu, Daniel E. Quevedo:
Stabilizing Scheduling Policies for Networked Control Systems. CoRR abs/1901.08353 (2019) - [i38]Lingying Huang, Alex S. Leong, Daniel E. Quevedo, Ling Shi:
Finite Time Encryption Schedule in the Presence of an Eavesdropper with Operation Cost. CoRR abs/1903.11763 (2019) - [i37]Adrian Redder, Arunselvan Ramaswamy, Daniel E. Quevedo:
Deep reinforcement learning for scheduling in large-scale networked control systems. CoRR abs/1905.05992 (2019) - [i36]Jingyi Lu, Alex S. Leong, Daniel E. Quevedo:
An event-triggered transmission scheduling strategy for remote state estimation in the presence of an eavesdropper. CoRR abs/1910.03759 (2019) - [i35]Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey:
A Game-Theoretic Approach to Covert Communications. CoRR abs/1911.00156 (2019) - 2018
- [j72]Prabhat Kumar Mishra, Debasish Chatterjee, Daniel E. Quevedo:
Sparse and constrained stochastic predictive control for networked systems. Autom. 87: 40-51 (2018) - [j71]Alex S. Leong, Subhrakanti Dey, Daniel E. Quevedo:
Transmission scheduling for remote state estimation and control with an energy harvesting sensor. Autom. 91: 54-60 (2018) - [j70]Moritz Schulze Darup, Adrian Redder, Iman Shames, Farhad Farokhi, Daniel E. Quevedo:
Towards Encrypted MPC for Linear Constrained Systems. IEEE Control. Syst. Lett. 2(2): 195-200 (2018) - [j69]Burak Demirel, Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl:
DeepCAS: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling. IEEE Control. Syst. Lett. 2(4): 737-742 (2018) - [j68]Prabhat Kumar Mishra, Debasish Chatterjee, Daniel E. Quevedo:
Stabilizing Stochastic Predictive Control Under Bernoulli Dropouts. IEEE Trans. Autom. Control. 63(6): 1489-1500 (2018) - [j67]Shuai Liu, Lihua Xie, Daniel E. Quevedo:
Event-Triggered Quantized Communication-Based Distributed Convex Optimization. IEEE Trans. Control. Netw. Syst. 5(1): 167-178 (2018) - [j66]Burak Demirel, Euhanna Ghadimi, Daniel E. Quevedo, Mikael Johansson:
Optimal Control of Linear Systems With Limited Control Actions: Threshold-Based Event-Triggered Control. IEEE Trans. Control. Netw. Syst. 5(3): 1275-1286 (2018) - [c63]Moritz Schulze Darup, Adrian Redder, Daniel E. Quevedo:
A fixed-point implementation of explicit MPC laws. ACC 2018: 749-755 - [c62]Alex S. Leong, Adrian Redder, Daniel E. Quevedo, Subhrakanti Dey:
On the Use of Artificial Noise for Secure State Estimation in the Presence of Eavesdroppers. ECC 2018: 325-330 - [i34]Burak Demirel, Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl:
DeepCAS: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling. CoRR abs/1803.02998 (2018) - [i33]Alex S. Leong, Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl, Ling Shi:
Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber-Physical Systems. CoRR abs/1809.05149 (2018) - 2017
- [j65]Kemi Ding, Yuzhe Li, Daniel E. Quevedo, Subhrakanti Dey, Ling Shi:
A multi-channel transmission schedule for remote state estimation under DoS attacks. Autom. 78: 194-201 (2017) - [j64]Daniel Dolz, Daniel E. Quevedo, Ignacio Peñarrocha, Alex S. Leong, Roberto Sanchis:
Co-design of jump estimators and transmission policies for wireless multi-hop networks with fading channels. Autom. 81: 68-74 (2017) - [j63]Kemi Ding, Subhrakanti Dey, Daniel E. Quevedo, Ling Shi:
Stochastic Game in Remote Estimation Under DoS Attacks. IEEE Control. Syst. Lett. 1(1): 146-151 (2017) - [j62]Prabhat Kumar Mishra, Debasish Chatterjee, Daniel E. Quevedo:
Output Feedback Stable Stochastic Predictive Control With Hard Control Constraints. IEEE Control. Syst. Lett. 1(2): 382-387 (2017) - [j61]Junfeng Wu, Yuzhe Li, Daniel E. Quevedo, Ling Shi:
Improved results on transmission power control for remote state estimation. Syst. Control. Lett. 107: 44-48 (2017) - [j60]Yuzhe Li, Fan Zhang, Daniel E. Quevedo, Vincent K. N. Lau, Subhrakanti Dey, Ling Shi:
Power Control of an Energy Harvesting Sensor for Remote State Estimation. IEEE Trans. Autom. Control. 62(1): 277-290 (2017) - [j59]Alex S. Leong, Subhrakanti Dey, Daniel E. Quevedo:
Sensor Scheduling in Variance Based Event Triggered Estimation With Packet Drops. IEEE Trans. Autom. Control. 62(4): 1880-1895 (2017) - [j58]Burak Demirel, Vijay Gupta, Daniel E. Quevedo, Mikael Johansson:
On the Trade-Off Between Communication and Control Cost in Event-Triggered Dead-Beat Control. IEEE Trans. Autom. Control. 62(6): 2973-2980 (2017) - [j57]Yuzhe Li, Daniel E. Quevedo, Subhrakanti Dey, Ling Shi:
SINR-Based DoS Attack on Remote State Estimation: A Game-Theoretic Approach. IEEE Trans. Control. Netw. Syst. 4(3): 632-642 (2017) - [j56]Nicolas Cardoso de Castro, Daniel E. Quevedo, Federica Garin, Carlos Canudas-de-Wit:
Energy-Aware Radio Chip Management for Wireless Control. IEEE Trans. Control. Syst. Technol. 25(6): 2121-2134 (2017) - [j55]Yuzhe Li, Daniel E. Quevedo, Subhrakanti Dey, Ling Shi:
A Game-Theoretic Approach to Fake-Acknowledgment Attack on Cyber-Physical Systems. IEEE Trans. Signal Inf. Process. over Networks 3(1): 1-11 (2017) - [c61]Yuqing Ni, Alex S. Leong, Daniel E. Quevedo, Ling Shi:
Game-theoretic pricing and selection with fading channels. ASCC 2017: 934-939 - [c60]Burak Demirel, Euhanna Ghadimi, Daniel E. Quevedo:
Sparsity-promoting iterative learning control for resource-constrained control systems. CDC 2017: 688-693 - [c59]Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey:
State estimation over Markovian packet dropping links in the presence of an eavesdropper. CDC 2017: 6616-6621 - [i32]Burak Demirel, Euhanna Ghadimi, Daniel E. Quevedo, Mikael Johansson:
Optimal control of linear systems with limited control actions: threshold-based event-triggered control. CoRR abs/1701.04871 (2017) - [i31]Daniel Dolz, Daniel E. Quevedo, Ignacio Peñarrocha, Alex S. Leong, Roberto Sanchis:
Co-design of jump estimators and transmission policies for wireless multi-hop networks with fading channels [Extended]. CoRR abs/1701.06535 (2017) - [i30]Alex S. Leong, Daniel E. Quevedo, Daniel Dolz, Subhrakanti Dey:
Remote State Estimation over Packet Dropping Links in the Presence of an Eavesdropper. CoRR abs/1702.02785 (2017) - [i29]Burak Demirel, Alex S. Leong, Vijay Gupta, Daniel E. Quevedo:
Trade-Offs in Stochastic Event-Triggered Control. CoRR abs/1708.02756 (2017) - [i28]Yuqing Ni, Alex S. Leong, Daniel E. Quevedo, Ling Shi:
Game-Theoretic Pricing and Selection with Fading Channels. CoRR abs/1710.05300 (2017) - 2016
- [j54]Sergio Lucia, Markus J. Kögel, Pablo Zometa, Daniel E. Quevedo, Rolf Findeisen:
Predictive control, embedded cyberphysical systems and systems of systems - A perspective. Annu. Rev. Control. 41: 193-207 (2016) - [j53]Merid Ljesnjanin, Dragan Nesic, Daniel E. Quevedo:
Robust stability of a class of Networked Control Systems. Autom. 73: 117-124 (2016) - [j52]Jan Østergaard, Daniel E. Quevedo:
Multiple descriptions for packetized predictive control. EURASIP J. Adv. Signal Process. 2016: 45 (2016) - [j51]Masaaki Nagahara, Jan Østergaard, Daniel E. Quevedo:
Discrete-time hands-off control by sparse optimization. EURASIP J. Adv. Signal Process. 2016: 76 (2016) - [j50]Debasish Chatterjee, Masaaki Nagahara, Daniel E. Quevedo, K. S. Mallikarjuna Rao:
Characterization of maximum hands-off control. Syst. Control. Lett. 94: 31-36 (2016) - [j49]Masaaki Nagahara, Daniel E. Quevedo, Dragan Nesic:
Maximum Hands-Off Control: A Paradigm of Control Effort Minimization. IEEE Trans. Autom. Control. 61(3): 735-747 (2016) - [j48]Alex S. Leong, Daniel E. Quevedo:
Kalman Filtering With Relays Over Wireless Fading Channels. IEEE Trans. Autom. Control. 61(6): 1643-1648 (2016) - [j47]Alex S. Leong, Daniel E. Quevedo, Anders Ahlén, Karl Henrik Johansson:
On Network Topology Reconfiguration for Remote State Estimation. IEEE Trans. Autom. Control. 61(12): 3842-3856 (2016) - [j46]Edwin G. W. Peters, Daniel E. Quevedo, Minyue Fu:
Controller and Scheduler Codesign for Feedback Control Over IEEE 802.15.4 Networks. IEEE Trans. Control. Syst. Technol. 24(6): 2016-2030 (2016) - [j45]Edwin G. W. Peters, Daniel E. Quevedo, Jan Østergaard:
Shaped Gaussian Dictionaries for Quantized Networked Control Systems With Correlated Dropouts. IEEE Trans. Signal Process. 64(1): 203-213 (2016) - [c58]Mohsen Zamani, Brett Ninness, Daniel E. Quevedo:
On the reachability property for networks of linear time-invariant subsystems. AuCC 2016: 27-31 - [c57]Kemi Ding, Daniel E. Quevedo, Subhrakanti Dey, Ling Shi:
A secure cross-layer design for remote estimation under DoS attack: When multi-sensor meets multi-channel. CDC 2016: 6297-6302 - [c56]Edwin G. W. Peters, Damián Marelli, Minyue Fu, Daniel E. Quevedo:
Unified approach to controller and MMSE estimator design with intermittent communications. CDC 2016: 6832-6837 - [c55]Prabhat Kumar Mishra, Debasish Chatterjee, Daniel E. Quevedo:
Stable stochastic predictive controller under unreliable up-link. ECC 2016: 2282-2287 - [c54]Alex S. Leong, Subhrakanti Dey, Daniel E. Quevedo:
Optimal transmission policies for variance based event triggered estimation with an energy harvesting sensor. EUSIPCO 2016: 225-229 - [c53]Roky Baidya, Ricardo P. Aguilera, Pablo Acuña, Ramón A. Delgado, Tobias Geyer, Daniel E. Quevedo, Toit Mouton:
Fast multistep finite control set model predictive control for transient operation of power converters. IECON 2016: 5039-5045 - [c52]Burak Demirel, Vijay Gupta, Daniel E. Quevedo, Mikael Johansson:
Threshold optimization of event-triggered multi-loop control systems. WODES 2016: 203-210 - [i27]Debasish Chatterjee, Masaaki Nagahara, Daniel E. Quevedo, K. S. Mallikarjuna Rao:
Characterization of maximum hands-off control. CoRR abs/1602.08834 (2016) - 2015
- [j44]Junfeng Wu, Yuzhe Li, Daniel E. Quevedo, Vincent K. N. Lau, Ling Shi:
Data-driven power control for state estimation: A Bayesian inference approach. Autom. 54: 332-339 (2015) - [j43]Isabel Jurado, Pablo Millán, Daniel E. Quevedo, Francisco R. Rubio:
Stochastic MPC with applications to process control. Int. J. Control 88(4): 792-800 (2015) - [j42]Isabel Jurado, Manuel G. Ortega, Daniel E. Quevedo, Francisco R. Rubio:
An H∞ suboptimal robust control approach for systems with uncertainties and data dropouts. Int. J. Syst. Sci. 46(11): 1971-1981 (2015) - [j41]Daniel E. Quevedo, Wann-Jiun Ma, Vijay Gupta:
Anytime Control Using Input Sequences With Markovian Processor Availability. IEEE Trans. Autom. Control. 60(2): 515-521 (2015) - [j40]Yuzhe Li, Ling Shi, Peng Cheng, Jiming Chen, Daniel E. Quevedo:
Jamming Attacks on Remote State Estimation in Cyber-Physical Systems: A Game-Theoretic Approach. IEEE Trans. Autom. Control. 60(10): 2831-2836 (2015) - [j39]Erik Henriksson, Daniel E. Quevedo, Edwin G. W. Peters, Henrik Sandberg, Karl Henrik Johansson:
Multiple-Loop Self-Triggered Model Predictive Control for Network Scheduling and Control. IEEE Trans. Control. Syst. Technol. 23(6): 2167-2181 (2015) - [j38]Sergio Vazquez, Abraham Marquez, Ricardo P. Aguilera, Daniel E. Quevedo, Jose Ignacio León Galván, Leopoldo García Franquelo:
Predictive Optimal Switching Sequence Direct Power Control for Grid-Connected Power Converters. IEEE Trans. Ind. Electron. 62(4): 2010-2020 (2015) - [j37]Ricardo P. Aguilera, Daniel E. Quevedo:
Predictive Control of Power Converters: Designs With Guaranteed Performance. IEEE Trans. Ind. Informatics 11(1): 53-63 (2015) - [j36]Ricardo P. Aguilera, Pablo Lezana, Daniel E. Quevedo:
Switched Model Predictive Control for Improved Transient and Steady-State Performance. IEEE Trans. Ind. Informatics 11(4): 968-977 (2015) - [j35]Steffi Knorn, Subhrakanti Dey, Anders Ahlén, Daniel E. Quevedo:
Distortion Minimization in Multi-Sensor Estimation Using Energy Harvesting and Energy Sharing. IEEE Trans. Signal Process. 63(11): 2848-2863 (2015) - [c51]Edwin G. W. Peters, Daniel E. Quevedo, Minyue Fu:
Co-design for control and scheduling over wireless industrial control networks. CDC 2015: 2459-2464 - [c50]K. Q. Huang, Thuy V. Dang, Keck Voon Ling, Daniel E. Quevedo:
Event-triggered anytime control with two controllers. CDC 2015: 4157-4162 - [c49]Merid Ljesnjanin, Dragan Nesic, Daniel E. Quevedo:
Uniform Global Asymptotic Stability of Networked Control Systems affected with packet dropouts and scheduling issues. CDC 2015: 5020-5025 - [c48]Yuzhe Li, Daniel E. Quevedo, Subhrakanti Dey, Ling Shi:
Fake-acknowledgment attack on ACK-based sensor power schedule for remote state estimation. CDC 2015: 5795-5800 - [c47]Alex S. Leong, Subhrakanti Dey, Daniel E. Quevedo:
On the optimality of threshold policies in event triggered estimation with packet drops. ECC 2015: 927-933 - [c46]Burak Demirel, Arda Aytekin, Daniel E. Quevedo, Mikael Johansson:
To wait or to drop: On the optimal number of retransmissions in wireless control. ECC 2015: 962-968 - [c45]Steffi Knorn, Subhrakanti Dey, Anders Ahlén, Daniel E. Quevedo:
Multi-sensor estimation using energy harvesting and energy sharing. ICC 2015: 4229-4234 - [c44]Sergio Vazquez, Abraham Marquez, Ricardo P. Aguilera, Daniel E. Quevedo, José I. Leon, Leopoldo García Franquelo:
Predictive direct power control for grid connected power converters with dc-link voltage dynamic reference design. ICIT 2015: 2327-2332 - [i26]Burak Demirel, Vijay Gupta, Daniel E. Quevedo, Mikael Johansson:
On the trade-off between control performance and communication cost in event-triggered control. CoRR abs/1501.00892 (2015) - [i25]Erik Henriksson, Daniel E. Quevedo, Edwin G. W. Peters, Henrik Sandberg, Karl Henrik Johansson:
Multiple Loop Self-Triggered Model Predictive Control for Network Scheduling and Control. CoRR abs/1502.03181 (2015) - [i24]Junfeng Wu, Yuzhe Li, Daniel E. Quevedo, Vincent K. N. Lau, Ling Shi:
Data-Driven Power Control for State Estimation: A Bayesian Inference Approach. CoRR abs/1503.07158 (2015) - [i23]Alex S. Leong, Daniel E. Quevedo:
Kalman Filtering With Relays Over Wireless Fading Channels. CoRR abs/1505.04885 (2015) - [i22]Mohsen Zamani, Brett Ninness, Daniel E. Quevedo:
On the Reachability of Networked Systems. CoRR abs/1505.06810 (2015) - [i21]Yuzhe Li, Daniel E. Quevedo, Subhrakanti Dey, Ling Shi:
Fake-Acknowledgment Attack on ACK-based Sensor Power Schedule for Remote State Estimation. CoRR abs/1506.07955 (2015) - [i20]Alex S. Leong, Subhrakanti Dey, Daniel E. Quevedo:
Sensor Scheduling in Variance Based Event Triggered Estimation with Packet Drops. CoRR abs/1511.04792 (2015) - 2014
- [j34]Merid Ljesnjanin, Daniel E. Quevedo, Dragan Nesic:
Packetized MPC with dynamic scheduling constraints and bounded packet dropouts. Autom. 50(3): 784-797 (2014) - [j33]Daniel E. Quevedo, Isabel Jurado:
Stability of Sequence-Based Control With Random Delays and Dropouts. IEEE Trans. Autom. Control. 59(5): 1296-1302 (2014) - [j32]Masaaki Nagahara, Daniel E. Quevedo, Jan Østergaard:
Sparse Packetized Predictive Control for Networked Control Over Erasure Channels. IEEE Trans. Autom. Control. 59(7): 1899-1905 (2014) - [j31]Daniel E. Quevedo, Vijay Gupta, Wann-Jiun Ma, Serdar Yüksel:
Stochastic Stability of Event-Triggered Anytime Control. IEEE Trans. Autom. Control. 59(12): 3373-3379 (2014) - [j30]Mojtaba Nourian, Alex S. Leong, Subhrakanti Dey, Daniel E. Quevedo:
An Optimal Transmission Strategy for Kalman Filtering Over Packet Dropping Links With Imperfect Acknowledgements. IEEE Trans. Control. Netw. Syst. 1(3): 259-271 (2014) - [j29]Daniel E. Quevedo, Jan Østergaard, Anders Ahlén:
Power Control and Coding Formulation for State Estimation With Wireless Sensors. IEEE Trans. Control. Syst. Technol. 22(2): 413-427 (2014) - [c43]Andres Lopez, Daniel E. Quevedo, Ricardo P. Aguilera, Tobias Geyer, Nikolaos Oikonomou:
Reference design for predictive control of modular multilevel converters. AuCC 2014: 239-244 - [c42]Yuzhe Li, Daniel E. Quevedo, Vincent K. N. Lau, Ling Shi:
Multi-sensor transmission power scheduling for remote state estimation under SINR model. CDC 2014: 1055-1060 - [c41]Daniel Dolz, Daniel E. Quevedo, Ignacio Peñarrocha, Roberto Sanchis:
A jump filter for uncertain dynamic systems with dropouts. CDC 2014: 5284-5289 - [i19]Yuzhe Li, Daniel E. Quevedo, Vincent K. N. Lau, Subhrakanti Dey, Ling Shi:
Transmission Power Scheduling for Energy Harvesting Sensor in Remote State Estimation. CoRR abs/1402.5784 (2014) - [i18]Mojtaba Nourian, Alex S. Leong, Subhrakanti Dey, Daniel E. Quevedo:
An Optimal Transmission Strategy for Kalman Filtering over Packet Dropping Links with Imperfect Acknowledgements. CoRR abs/1402.6633 (2014) - [i17]Daniel E. Quevedo, Wann-Jiun Ma, Vijay Gupta:
Anytime Control using Input Sequences with Markovian Processor Availability. CoRR abs/1405.0751 (2014) - [i16]Masaaki Nagahara, Daniel E. Quevedo, Dragan Nesic:
Hands-Off Control as Green Control. CoRR abs/1407.2377 (2014) - [i15]Masaaki Nagahara, Daniel E. Quevedo, Dragan Nesic:
Maximum Hands-Off Control: A Paradigm of Control Effort Minimization. CoRR abs/1408.3025 (2014) - 2013
- [j28]Daniel E. Quevedo, Karl Henrik Johansson, Anders Ahlén, Isabel Jurado:
Adaptive controller placement for wireless sensor-actuator networks with erasure channels. Autom. 49(11): 3458-3466 (2013) - [j27]Daniel E. Quevedo, Vijay Gupta:
Sequence-Based Anytime Control. IEEE Trans. Autom. Control. 58(2): 377-390 (2013) - [j26]Daniel E. Quevedo, Anders Ahlén, Karl Henrik Johansson:
State Estimation Over Sensor Networks With Correlated Wireless Fading Channels. IEEE Trans. Autom. Control. 58(3): 581-593 (2013) - [j25]Daniel E. Quevedo, Jan Østergaard, Eduardo I. Silva, Dragan Nesic:
Correction to "Packetized Predictive Control of Stochastic Systems Over Bit-Rate Limited Channels With Packet Loss". IEEE Trans. Autom. Control. 58(7): 1869-1872 (2013) - [j24]Ricardo P. Aguilera, Daniel E. Quevedo:
Stability Analysis of Quadratic MPC With a Discrete Input Alphabet. IEEE Trans. Autom. Control. 58(12): 3190-3196 (2013) - [j23]Ricardo P. Aguilera, Pablo Lezana, Daniel E. Quevedo:
Finite-Control-Set Model Predictive Control With Improved Steady-State Performance. IEEE Trans. Ind. Informatics 9(2): 658-667 (2013) - [j22]Yuzhe Li, Daniel E. Quevedo, Vincent K. N. Lau, Ling Shi:
Optimal Periodic Transmission Power Schedules for Remote Estimation of ARMA Processes. IEEE Trans. Signal Process. 61(24): 6164-6174 (2013) - [c40]Alex S. Leong, Daniel E. Quevedo:
On the use of a relay for Kalman filtering over packet dropping links. ACC 2013: 3320-3325 - [c39]Masaaki Nagahara, Daniel E. Quevedo, Dragan Nesic:
Maximum hands-off control and L1 optimality. CDC 2013: 3825-3830 - [c38]Yuzhe Li, Daniel E. Quevedo, Vincent K. N. Lau, Ling Shi:
Online sensor transmission power schedule for remote state estimation. CDC 2013: 4000-4005 - [c37]Merid Ljesnjanin, Daniel E. Quevedo, Dragan Nesic:
Robustness of networked control systems with multiple actuator-links and bounded packet dropouts. CDC 2013: 5963-5968 - [c36]Jan Østergaard, Daniel E. Quevedo:
Multiple Description Coding for Closed Loop Systems over Erasure Channels. DCC 2013: 311-320 - [c35]Pablo Lezana, Margarita Norambuena, Ricardo P. Aguilera, Daniel E. Quevedo:
Dual-stage model predictive control for Flying Capacitor Converters. IECON 2013: 5794-5799 - [i14]Masaaki Nagahara, Daniel E. Quevedo, Dragan Nesic:
Maximum-Hands-Off Control and L1 Optimality. CoRR abs/1307.8232 (2013) - [i13]Masaaki Nagahara, Daniel E. Quevedo, Jan Østergaard:
Sparse Packetized Predictive Control for Networked Control over Erasure Channels. CoRR abs/1307.8242 (2013) - [i12]Masaaki Nagahara, Daniel E. Quevedo, Jan Østergaard:
Packetized Predictive Control for Rate-Limited Networks via Sparse Representation. CoRR abs/1308.0002 (2013) - [i11]Masaaki Nagahara, Daniel E. Quevedo, Jan Østergaard:
Sparsely-Packetized Predictive Control by Orthogonal Matching Pursuit. CoRR abs/1308.0518 (2013) - [i10]Masaaki Nagahara, Daniel E. Quevedo:
Sparse Representations for Packetized Predictive Networked Control. CoRR abs/1308.1590 (2013) - [i9]Daniel E. Quevedo, Anders Ahlén, Karl Henrik Johansson:
State Estimation over Sensor Networks with Correlated Wireless Fading Channels. CoRR abs/1308.1725 (2013) - [i8]Daniel E. Quevedo, Karl Henrik Johansson, Anders Ahlén, Isabel Jurado:
Adaptive Controller Placement for Wireless Sensor-Actuator Networks with Erasure Channels. CoRR abs/1308.1744 (2013) - [i7]Daniel E. Quevedo, Jan Østergaard, Anders Ahlén:
Power Control and Coding Formulation for State Estimation with Wireless Sensors. CoRR abs/1308.1745 (2013) - [i6]Daniel E. Quevedo, Vijay Gupta:
Sequence-based Anytime Control. CoRR abs/1308.1747 (2013) - [i5]Masaaki Nagahara, Daniel E. Quevedo, Takahiro Matsuda, Kazunori Hayashi:
Compressive Sampling for Networked Feedback Control. CoRR abs/1308.2291 (2013) - [i4]Masaaki Nagahara, Daniel E. Quevedo, Jan Østergaard, Takahiro Matsuda, Kazunori Hayashi:
Sparse Command Generator for Remote Control. CoRR abs/1308.2592 (2013) - [i3]Daniel E. Quevedo, Isabel Jurado:
Stability of Sequence-Based Control with Random Delays and Dropouts. CoRR abs/1311.1568 (2013) - [i2]Daniel E. Quevedo, Vijay Gupta, Wann-Jiun Ma, Serdar Yüksel:
Stochastic Stability of Event-triggered Anytime Control. CoRR abs/1312.2390 (2013) - 2012
- [j21]Daniel E. Quevedo, Anders Ahlén, Alex S. Leong, Subhrakanti Dey:
On Kalman filtering over fading wireless channels with controlled transmission powers. Autom. 48(7): 1306-1316 (2012) - [j20]Daniel E. Quevedo, Dragan Nesic:
Robust stability of packetized predictive control of nonlinear systems with disturbances and Markovian packet losses. Autom. 48(8): 1803-1811 (2012) - [c34]Marcus Reble, Daniel E. Quevedo, Frank Allgöwer:
A unifying framework for stability in MPC using a generalized integral terminal cost. ACC 2012: 1211-1216 - [c33]Masaaki Nagahara, Daniel E. Quevedo, Jan Østergaard:
Packetized predictive control for rate-limited networks via sparse representation. CDC 2012: 1362-1367 - [c32]Marcus Reble, Daniel E. Quevedo, Frank Allgöwer:
Improved stability conditions for unconstrained nonlinear model predictive control by using additional weighting terms. CDC 2012: 2625-2630 - [c31]Nicolas Cardoso de Castro, Daniel E. Quevedo, Federica Garin, Carlos Canudas de Wit:
Smart energy-aware sensors for event-based control. CDC 2012: 7224-7229 - [c30]Masaaki Nagahara, Daniel E. Quevedo, Takahiro Matsuda, Kazunori Hayashi:
Compressive sampling for networked feedback control. ICASSP 2012: 2733-2736 - 2011
- [j19]Yumiko Ishido, Kiyotsugu Takaba, Daniel E. Quevedo:
Stability analysis of networked control systems subject to packet-dropouts and finite-level quantization. Syst. Control. Lett. 60(5): 325-332 (2011) - [j18]Daniel E. Quevedo, Dragan Nesic:
Input-to-State Stability of Packetized Predictive Control Over Unreliable Networks Affected by Packet-Dropouts. IEEE Trans. Autom. Control. 56(2): 370-375 (2011) - [j17]Claus Müller, Daniel E. Quevedo, Graham C. Goodwin:
How Good is Quantized Model Predictive Control With Horizon One? IEEE Trans. Autom. Control. 56(11): 2623-2638 (2011) - [j16]Daniel E. Quevedo, Jan Østergaard, Dragan Nesic:
Packetized Predictive Control of Stochastic Systems Over Bit-Rate Limited Channels With Packet Loss. IEEE Trans. Autom. Control. 56(12): 2854-2868 (2011) - [j15]Jan Østergaard, Daniel E. Quevedo, Jesper Jensen:
Real-Time Perceptual Moving-Horizon Multiple-Description Audio Coding. IEEE Trans. Signal Process. 59(9): 4286-4299 (2011) - [c29]Daniel E. Quevedo, Vijay Gupta:
Stability of sequence-based anytime control with Markovian processor availability. AuCC 2011: 56-61 - [c28]Jan Østergaard, Daniel E. Quevedo:
Multiple descriptions for packetized predictive control over erasure channels. ICCA 2011: 165-170 - [c27]Marcus Reble, Daniel E. Quevedo, Frank Allgöwer:
Stochastic stability and performance estimates of packetized unconstrained model predictive control for networked control systems. ICCA 2011: 171-176 - [c26]Masaaki Nagahara, Daniel E. Quevedo, Jan Østergaard, Takahiro Matsuda, Kazunori Hayashi:
Sparse command generator for remote control. ICCA 2011: 1055-1059 - 2010
- [j14]Graham C. Goodwin, David Q. Mayne, Keng-Yuan Chen, Colin Coates, Galina Mirzaeva, Daniel E. Quevedo:
An introduction to the control of switching electronic systems. Annu. Rev. Control. 34(2): 209-220 (2010) - [j13]Eduardo I. Silva, Graham C. Goodwin, Daniel E. Quevedo:
Control system design subject to SNR constraints. Autom. 46(2): 428-436 (2010) - [j12]Daniel E. Quevedo, Anders Ahlén, Jan Østergaard:
Energy efficient state estimation with wireless sensors through the use of predictive power control and coding. IEEE Trans. Signal Process. 58(9): 4811-4823 (2010) - [c25]Vijay Gupta, Daniel E. Quevedo:
On anytime control of nonlinear processes through calculation of control sequences. CDC 2010: 7564-7569 - [c24]Jan Østergaard, Daniel E. Quevedo, Anders Ahlén:
Predictive power control for dynamic state estimation over wireless sensor networks with relays. EUSIPCO 2010: 194-198
2000 – 2009
- 2009
- [j11]Pablo Lezana, Ricardo P. Aguilera, Daniel E. Quevedo:
Model Predictive Control of an Asymmetric Flying Capacitor Converter. IEEE Trans. Ind. Electron. 56(6): 1839-1846 (2009) - [j10]Daniel E. Quevedo, Helmut Bölcskei, Graham C. Goodwin:
Quantization of Filter Bank Frame Expansions Through Moving Horizon Optimization. IEEE Trans. Signal Process. 57(2): 503-515 (2009) - [c23]Daniel E. Quevedo, Jan Østergaard:
Quantized predictive control over erasure channels. CDC 2009: 2076-2081 - [c22]Eduardo I. Silva, Graham C. Goodwin, Daniel E. Quevedo:
On the design of control systems over unreliable channels. ECC 2009: 377-382 - [c21]Ricardo P. Aguilera, Daniel E. Quevedo:
Predictive control formulation for achieving a reduced finite control set in flying capacitor converters. ECC 2009: 3955-3960 - [c20]Daniel E. Quevedo, Anders Ahlén, Jan Østergaard, Graham C. Goodwin:
Innovations-based state estimation with wireless sensor networks. ECC 2009: 4858-4864 - [c19]Jan Østergaard, Daniel E. Quevedo, Jesper Jensen:
Low delay moving-horizon multiple-description audio coding forwireless hearing aids. ICASSP 2009: 21-24 - [c18]Jan Østergaard, Daniel E. Quevedo, Anders Ahlén:
Predictive power control and multiple-description coding for wireless sensor networks. ICASSP 2009: 2785-2788 - 2008
- [j9]Graham C. Goodwin, Daniel E. Quevedo, Eduardo I. Silva:
Architectures and coder design for networked control systems. Autom. 44(1): 248-257 (2008) - [j8]Daniel E. Quevedo, Eduardo I. Silva, Graham C. Goodwin:
Control over unreliable networks affected by packet erasures and variable transmission delays. IEEE J. Sel. Areas Commun. 26(4): 672-685 (2008) - [j7]Patricio Cortes, Marian P. Kazmierkowski, Ralph Kennel, Daniel E. Quevedo, José R. Rodríguez:
Predictive Control in Power Electronics and Drives. IEEE Trans. Ind. Electron. 55(12): 4312-4324 (2008) - [j6]Milan S. Derpich, Eduardo I. Silva, Daniel E. Quevedo, Graham C. Goodwin:
On Optimal Perfect Reconstruction Feedback Quantizers. IEEE Trans. Signal Process. 56(8-2): 3871-3890 (2008) - [c17]Daniel E. Quevedo, Anders Ahlén:
A predictive power control scheme for energy efficient state estimation via wireless sensor networks. CDC 2008: 1103-1108 - [c16]Eduardo I. Silva, Milan S. Derpich, Jan Østergaard, Daniel E. Quevedo:
Simple coding for achieving mean square stability over bit-rate limited channels. CDC 2008: 2698-2703 - [c15]Milan S. Derpich, Daniel E. Quevedo, Graham C. Goodwin:
Conditions for optimality of scalar feedback quantization. ICASSP 2008: 3749-3752 - [i1]Milan S. Derpich, Jan Østergaard, Daniel E. Quevedo:
Achieving the Quadratic Gaussian Rate-Distortion Function for Source Uncorrelated Distortions. CoRR abs/0801.1718 (2008) - 2007
- [j5]Daniel E. Quevedo, Claus Müller, Graham C. Goodwin:
Conditions for optimality of Naïve quantized finite horizon control. Int. J. Control 80(5): 706-720 (2007) - [j4]Daniel E. Quevedo, Graham C. Goodwin, José A. De Doná:
Multistep Detector for Linear ISI-Channels Incorporating Degrees of Belief in Past Estimates. IEEE Trans. Commun. 55(11): 2092-2103 (2007) - [c14]Daniel E. Quevedo, Eduardo I. Silva, Graham C. Goodwin:
Packetized Predictive Control over Erasure Channels. ACC 2007: 1003-1008 - [c13]Eduardo I. Silva, Brendan P. McGrath, Daniel E. Quevedo, Graham C. Goodwin:
Predictive Control of a Flying Capacitor Converter. ACC 2007: 3763-3768 - [c12]Eduardo I. Silva, Daniel E. Quevedo, Graham C. Goodwin:
Optimal coding for bit-rate limited networked control systems in the presence of data loss. CDC 2007: 665-670 - [c11]Meng Wang, Daniel E. Quevedo, Graham C. Goodwin, Brian S. Krongold:
OFDMA Uplink PAR Reduction via Tone Reservation. GLOBECOM 2007: 3802-3806 - 2006
- [c10]Meng Wang, Daniel E. Quevedo, Graham C. Goodwin:
Joint Data Detection and Channel Estimation for MIMO-OFDM Systems via EM Algorithm and Sphere Decoding. GLOBECOM 2006 - [c9]Milan S. Derpich, Daniel E. Quevedo, Graham C. Goodwin, Arie Feuer:
Quantization and Sampling of Not Necessarily Band-Limited Signals. ICASSP (3) 2006: 396-399 - 2005
- [j3]Daniel E. Quevedo, Graham C. Goodwin:
Multistep optimal analog-to-digital conversion. IEEE Trans. Circuits Syst. I Regul. Pap. 52-I(3): 503-515 (2005) - [j2]Daniel E. Quevedo, Graham C. Goodwin:
Moving horizon design of discrete coefficient FIR filters. IEEE Trans. Signal Process. 53(6): 2262-2267 (2005) - 2004
- [j1]Graham C. Goodwin, Hernan Haimovich, Daniel E. Quevedo, James S. Welsh:
A moving horizon approach to Networked Control system design. IEEE Trans. Autom. Control. 49(9): 1427-1445 (2004) - [c8]Daniel E. Quevedo, Graham C. Goodwin:
Control of EMI from switch-mode power supplies via multi-step optimization. ACC 2004: 390-395 - [c7]Daniel E. Quevedo, Graham C. Goodwin, Helmut Bölcskei:
Multi-step optimal quantization in oversampled filter banks. CDC 2004: 1442-1447 - 2003
- [c6]Graham C. Goodwin, Daniel E. Quevedo, José A. De Doná:
An application of receding horizon control to estimation with quantized coefficients. ACC 2003: 2703-2707 - [c5]Daniel E. Quevedo, Graham C. Goodwin:
Audio quantization from a receding horizon control perspective. ACC 2003: 4131-4136 - [c4]Daniel E. Quevedo, Graham C. Goodwin, James S. Welsh:
Minimizing down-link traffic in networked control systems via optimal control techniques. CDC 2003: 1200-1205 - [c3]Hernan Haimovich, Graham C. Goodwin, Daniel E. Quevedo:
Moving horizon Monte Carlo state estimation for linear systems with output quantization. CDC 2003: 4859-4864 - 2002
- [c2]Daniel E. Quevedo, José A. De Doná, Graham C. Goodwin:
On the dynamics of receding horizon linear quadratic finite alphabet control loops. CDC 2002: 2929-2934 - 2000
- [c1]Daniel E. Quevedo, Mario E. Salgado:
Robustification of model predictive control. CDC 2000: 178-180
Coauthor Index
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last updated on 2024-12-10 20:50 CET by the dblp team
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dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
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