The adaptive hybrid function projective synchronization AHFPS of different chaotic systems with unknown time-varying parameters is investigated. Based on the Lyapunov stability theory and adaptive bounding technique, the robust adaptive control law and the parameters update law are derived to make the states of two different chaotic systems asymptotically synchronized. In the control strategy, ...

Online approximation of an infinite horizon optimal path-following strategy for a kinematic unicycle is considered. The solution to the optimal control problem is approximated using an approximate dynamic programming technique that uses concurrent-learning-based adaptive update laws to estimate the unknown value function. The developed controller overcomes challenges with the approximation of t...

In deterministic systems, reinforcement learningbased online approximate optimal control methods typically require a restrictive persistence of excitation (PE) condition for convergence. This paper presents a concurrent learningbased solution to the online approximate optimal regulation problem that eliminates the need for PE. The development is based on the observation that given a model of th...

In this paper, we design a nonlinear controller for the kinematic model of an underactuated rigid spacecraft that ensures uniform, ultimately bounded (UUB) tracking provided the initial errors are selected sufficiently small. The result is achieved via a judicious formulation of the spacecraft kinematics and the novel design of a Lyapunov-based controller. We also discuss how standard backstepp...

This paper provides new stability results for Action-Dependent Heuristic Dynamic Programming (ADHDP), using a control algorithm that iteratively improves an internal model of the external world in the autonomous system based on its continuous interaction with the environment. We extend previous results for ADHDP control to the case of general multi-layer neural networks with deep learning acros...

This paper provides new stability results for Action-Dependent Heuristic Dynamic Programming (ADHDP), using a control algorithm that iteratively improves an internal model of the external world in the autonomous system based on its continuous interaction with the environment. We extend previous results by ADHDP control to the case of general multi-layer neural networks with deep learning across...

Abstract This paper presents a novel compensator-critic structure-based event-triggered decentralized tracking control of modular robot manipulators (MRMs). On the basis subsystem dynamics under joint torque feedback (JTF) technique, proposed error fusion function, which includes position and velocity error, is utilized to construct performance index function. By analyzing dynamic uncertainties...

This paper considers point-to-point navigation of underactuated ships where only surge force and yaw moment are available. In general, a ship’s sway motion satisfies a passive-boundedness property which is expressed in terms of a Lyapunov function. Under this kind of consideration, a certain concise nonlinear scheme is proposed to guarantee the closed-loop system to be uniformly ultimately boun...

An approximate optimal indirect regulation problem is considered for two nonlinear uncertain agents. influencing agent tasked with optimally intercepting and directing a roaming to goal location. The not directly controlled by the agent, but instead moves based on some interaction dynamic. To overcome this challenge, virtual controller designed yield desired influence agent. In addition, an dyn...

In this paper, a robust PID control scheme is proposed for Micro-Electro-Mechanical-Systems (MEMS) optical switches. The proposed approach is designed in a way which solves two challenging and important problems. The first one is successful reference tracking and the second is mitigating the system nonlinearities. The overall system composed of nonlinear MEMS dynamics and the PID controller is ...