Multiple Model Adaptive Tracking Control Based on Adaptive Dynamic Programming

Kang Wang,Yang Li,Xiaoli Li

doi:10.1155/2016/6023892

Abstract

Adaptive dynamic programming (ADP) has been tested as an effective method for optimal control of nonlinear system. However, as the structure of ADP requires control input to satisfy the initial admissible control condition, the control performance may be deteriorated due to abrupt parameter change or system failure. In this paper, we introduce the multiple models idea into ADP, multiple subcontrollers run in parallel to supply multiple initial conditions for different environments, and a switching index is set up to decide the appropriate initial conditions for current system. By taking this strategy, the proposed multiple model ADP achieves optimal control for system with jumping parameters. The convergence of multiple model adaptive control based on ADP is proved and the simulation shows that the proposed method can improve the transient response of system effectively.

Highlights

In recent years, multiple model adaptive control (MMAC) has been a research focus on improving the transient response of nonlinear system
Neural networks (NNs) and fuzzy logic are widely used to handle the control problem of nonlinear systems owing to their fast adaptability and excellent approximation ability
(5) Once there is model switch showed by switching index function, state and control of corresponding subcontroller are selected as the initial condition of the main Adaptive dynamic programming (ADP) controller for the new stage

Summary

Introduction

Multiple model adaptive control (MMAC) has been a research focus on improving the transient response of nonlinear system. From 1990s, multiple model adaptive control based on index switching function has obtained satisfying results for linear system, linear time-variant system with jumping parameters, and stochastic system with stochastic disturbance. Neural networks (NNs) and fuzzy logic are widely used to handle the control problem of nonlinear systems owing to their fast adaptability and excellent approximation ability. Once there is a model switching, corresponding controller will be selected to provide its current state and control signal as the initial condition of system Based on this idea, we design multiple fixed models if the submodels are precisely known.

Problem Description

Trajectory Tracking Based on ADP

Multiple Model Control Scheme Based on ADP

Simulation

Conclusion