This paper tackles the problem of coordinated vision-based tracking of a ground target by a fleet... more This paper tackles the problem of coordinated vision-based tracking of a ground target by a fleet of multiple UAVs that exchange information over a supporting time-varying network. The objective of this work is to formulate decentralized control algorithms that enable multiple vehicles to follow a target while coordinating their phase separation. A typical scenario involves multiple aerial surveillance UAVs which are required to monitor a moving ground object (target tracking), while maintaining a desired inter-vehicle separation (coordination). To solve the tracking problem, the yaw rate of each vehicle is used as control input, while the ground speeds are adjusted to achieve coordination. It is assumed that the UAVs are equipped with an internal autopilot, which is able to track yaw rate and ground speed commands. The performance of the coordinated vision-based tracking algorithm is evaluated as a function of target's velocity, tracking performance of the onboard autopilot, and the quality of service of the communication network.
IEEE Transactions on Automatic Control, Sep 1, 2015
ABSTRACT L1 adaptive control is an appealing technology for control of systems in the presence of... more ABSTRACT L1 adaptive control is an appealing technology for control of systems in the presence of uncertainties. It addresses the issue of providing guaranteed transient performance and robustness for a class of adaptive architectures. This paper studies the real-time output-feedback L1 adaptive tracking over real-time networks. Event-triggered communication protocols are presented to schedule data transmission between the plant and the controller. We show that under the proposed scheme the difference between the states of the resulting networked control systems and an ideal model is uniformly bounded, and the bound can be further reduced by improving the communication quality. Stability conditions, in terms of event thresholds, allowable transmission delays, and control parameters, are provided, which can serve as guidance in real-time scheduling.
We present a direct method for the solution of nonlinear optimal control problems based on Bernst... more We present a direct method for the solution of nonlinear optimal control problems based on Bernstein polynomial approximations. We show, using a rigorous setting, that the proposed method yields consistent approximations of time continuous optimal control problems. We demonstrate that the method can also be used for the estimation of optimal control problems costates. This result leads to the formulation of the Covector Mapping Theorem for Bernstein polynomial approximation. Finally, we exploit the numerical and geometric properties of Bernstein polynomials, and illustrate the advantages of the method through numerical examples.
This paper considers continuous-time linear stochastic systems driven by Wiener process inputs, w... more This paper considers continuous-time linear stochastic systems driven by Wiener process inputs, which also have unknown system parameters and disturbances. ℒ1 adaptive controller is offered for this class of systems, and the performance of the closed-loop system is analyzed. The system output is shown to track that of a stable reference system, and the performance bounds are shown to be determined by the adaptation rate and the incremental variance of the Wiener process. Simulations demonstrate the theoretical results.
This paper presents the L1 adaptive control architecture for nonlinear strict feedback systems in... more This paper presents the L1 adaptive control architecture for nonlinear strict feedback systems in the presence of unknown high frequency control gain and unknown time-varying nonlinearities.We prove that the L1 adaptive control architecture ensures guaranteed transient response for system's input and output signals simultaneously. Simulations of an airplane short period dynamics verify the theoretical findings.
Autonomous operation of UAS holds promise for greater productivity of atmospheric science mission... more Autonomous operation of UAS holds promise for greater productivity of atmospheric science missions. However, several challenges need to be overcome before such missions can be made autonomous. This paper presents a framework for safe autonomous operations of multiple vehicles, particularly suited for atmospheric science missions. The framework revolves around the use of piecewise Bezier curves for trajectory representation, which in conjunction with path-following and time-coordination algorithms, allows for safe coordinated operations of multiple vehicles.
This paper tackles the problem of coordinated vision-based tracking of a ground target by a fleet... more This paper tackles the problem of coordinated vision-based tracking of a ground target by a fleet of multiple UAVs that exchange information over a supporting time-varying network. The objective of this work is to formulate decentralized control algorithms that enable multiple vehicles to follow a target while coordinating their phase separation. A typical scenario involves multiple aerial surveillance UAVs which are required to monitor a moving ground object (target tracking), while maintaining a desired inter-vehicle separation (coordination). To solve the tracking problem, the yaw rate of each vehicle is used as control input, while the ground speeds are adjusted to achieve coordination. It is assumed that the UAVs are equipped with an internal autopilot, which is able to track yaw rate and ground speed commands. The performance of the coordinated vision-based tracking algorithm is evaluated as a function of target's velocity, tracking performance of the onboard autopilot, and the quality of service of the communication network.
IEEE Transactions on Automatic Control, Sep 1, 2015
ABSTRACT L1 adaptive control is an appealing technology for control of systems in the presence of... more ABSTRACT L1 adaptive control is an appealing technology for control of systems in the presence of uncertainties. It addresses the issue of providing guaranteed transient performance and robustness for a class of adaptive architectures. This paper studies the real-time output-feedback L1 adaptive tracking over real-time networks. Event-triggered communication protocols are presented to schedule data transmission between the plant and the controller. We show that under the proposed scheme the difference between the states of the resulting networked control systems and an ideal model is uniformly bounded, and the bound can be further reduced by improving the communication quality. Stability conditions, in terms of event thresholds, allowable transmission delays, and control parameters, are provided, which can serve as guidance in real-time scheduling.
We present a direct method for the solution of nonlinear optimal control problems based on Bernst... more We present a direct method for the solution of nonlinear optimal control problems based on Bernstein polynomial approximations. We show, using a rigorous setting, that the proposed method yields consistent approximations of time continuous optimal control problems. We demonstrate that the method can also be used for the estimation of optimal control problems costates. This result leads to the formulation of the Covector Mapping Theorem for Bernstein polynomial approximation. Finally, we exploit the numerical and geometric properties of Bernstein polynomials, and illustrate the advantages of the method through numerical examples.
This paper considers continuous-time linear stochastic systems driven by Wiener process inputs, w... more This paper considers continuous-time linear stochastic systems driven by Wiener process inputs, which also have unknown system parameters and disturbances. ℒ1 adaptive controller is offered for this class of systems, and the performance of the closed-loop system is analyzed. The system output is shown to track that of a stable reference system, and the performance bounds are shown to be determined by the adaptation rate and the incremental variance of the Wiener process. Simulations demonstrate the theoretical results.
This paper presents the L1 adaptive control architecture for nonlinear strict feedback systems in... more This paper presents the L1 adaptive control architecture for nonlinear strict feedback systems in the presence of unknown high frequency control gain and unknown time-varying nonlinearities.We prove that the L1 adaptive control architecture ensures guaranteed transient response for system's input and output signals simultaneously. Simulations of an airplane short period dynamics verify the theoretical findings.
Autonomous operation of UAS holds promise for greater productivity of atmospheric science mission... more Autonomous operation of UAS holds promise for greater productivity of atmospheric science missions. However, several challenges need to be overcome before such missions can be made autonomous. This paper presents a framework for safe autonomous operations of multiple vehicles, particularly suited for atmospheric science missions. The framework revolves around the use of piecewise Bezier curves for trajectory representation, which in conjunction with path-following and time-coordination algorithms, allows for safe coordinated operations of multiple vehicles.
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