Nearly optimal control for nonlinear systems with dead-zone control input based on the iterative ADP approach

Authors:
Dehua Zhang;Derong Liu;Qinglai Wei
Affiliations:
State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China;State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China;State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
Year:
2012

Citing 6
Cited 0

Adaptive Control of Systems with Actuator and Sensor Nonlinearities

Adaptive Control of Systems with Actuator and Sensor Nonlinearities
Neural-network-based near-optimal control for a class of discrete-time affine nonlinear systems with control constraints

IEEE Transactions on Neural Networks
Issues on Stability of ADP Feedback Controllers for Dynamical Systems

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach

Automatica (Journal of IFAC)
Adaptive critic designs

IEEE Transactions on Neural Networks
Neural network control of a class of nonlinear systems with actuator saturation

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper focuses on a class of unknown discrete-time nonlinear systems with dead-zone control constraints based on adaptive dynamic programming (ADP). The discrete-time Hamilton-Jacobi-Bellman (DTHJB) equation corresponding to the dead-zone control input is formulated. Based on ADP technique, a new cost function is proposed that solves the optimal control with dead zone constraints effectively. It shows that this algorithm allows the implementation of the optimal control without knowing nonlinear affine system model and dead-zone dynamics. Finally, a simulation example is provided to verify the effectiveness of the proposed iterative algorithm.