Journal ArticleDOI
Disturbance observer-based robust missile autopilot design with full-state constraints via adaptive dynamic programming
Jingliang Sun,Chunsheng Liu +1 more
TLDR
A robust optimal control method for longitudinal dynamics of missile systems with full-state constraints suffering from mismatched disturbances is developed by using adaptive dynamic programming (ADP) technique to learn an adaptive optimal controller for nominal systems.Abstract:
This paper aims to develop a robust optimal control method for longitudinal dynamics of missile systems with full-state constraints suffering from mismatched disturbances by using adaptive dynamic programming (ADP) technique. First, the constrained states are mapped by smooth functions, thus, the considered systems become nonlinear systems without state constraints subject to unknown approximation error. In order to estimate the unknown disturbances, a nonlinear disturbance observer (NDO) is designed. Based on the output of disturbance observer, an integral sliding mode controller (ISMC) is derived to counteract the effects of disturbances and unknown approximation error, thus ensuring the stability of nonlinear systems. Subsequently, the ADP technique is utilized to learn an adaptive optimal controller for the nominal systems, in which a critic network is constructed with a novel weight update law. By utilizing the Lyapunov's method, the stability of the closed-loop system and the convergence of the estimation weight for critic network are guaranteed. Finally, the feasibility and effectiveness of the proposed controller are demonstrated by using longitudinal dynamics of a missile.read more
Citations
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Journal ArticleDOI
Online Barrier-Actor-Critic Learning for H∞ Control with Full-State Constraints and Input Saturation
TL;DR: A novel barrier-actor-critic algorithm is presented for adaptive optimal learning while guaranteeing the full-state constraints and input saturation and it is proven that the closed-loop signals remain bounded during the online learning phase.
Journal ArticleDOI
Sliding-Mode Surface-Based Approximate Optimal Control for Uncertain Nonlinear Systems With Asymptotically Stable Critic Structure
Bo Zhao,Derong Liu,Cesare Alippi +2 more
TL;DR: A sliding-mode surface (SMS)-based approximate optimal control scheme for a large class of nonlinear systems affected by unknown mismatched perturbations and the stability is proved based on the Lyapunov’s direct method is developed.
Journal ArticleDOI
Reinforcement learning control for underactuated surface vessel with output error constraints and uncertainties
TL;DR: A stability analysis is proposed to prove that the boundedness of system signals and the desired tracking performance can be guaranteed and the effectiveness and feasibility of the proposed controller is illustrated.
Journal ArticleDOI
A novel active fault-tolerant control for spacecrafts with full state constraints and input saturation
TL;DR: An active fault-tolerant control system for spacecrafts subject to model uncertainty, external disturbance and actuator fault simultaneously, using a robust fault observer with a simple structure is proposed.
Journal ArticleDOI
Backstepping-based adaptive dynamic programming for missile-target guidance systems with state and input constraints
Jingliang Sun,Chunsheng Liu +1 more
TL;DR: A novel backstepping-based adaptive dynamic programming (ADP) method is developed to solve the problem of intercepting a maneuver target in the presence of full-state and input constraints, by utilizing Lyapunov's direct method.
References
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Reference BookDOI
Neural Network Control of Robot Manipulators and Nonlinear Systems
TL;DR: This graduate text provides an authoritative account of neural network (NN) controllers for robotics and nonlinear systems and gives the first textbook treatment of a general and streamlined design procedure for NN controllers.
Journal ArticleDOI
Disturbance observer based control for nonlinear systems
TL;DR: This work presents a general framework for nonlinear systems subject to disturbances using disturbance observer based control (DOBC) techniques and develops a nonlinear disturbance observer for disturbances generated by an exogenous system.
Journal ArticleDOI
Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach
Murad Abu-Khalaf,Frank L. Lewis +1 more
TL;DR: It is shown that the constrained optimal control law has the largest region of asymptotic stability (RAS) and the result is a nearly optimal constrained state feedback controller that has been tuned a priori off-line.
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