Decentralized prescribed performance adaptive tracking control for Markovian jump uncertain nonlinear systems with input saturation |
| |
| Authors: | Ru Chang Yiming Fang Le Liu Jianxiong Li |
| |
| Affiliation: | 1. Key Lab of Industrial Computer Control Engineering of Hebei Province, School of Electrical Engineering, Yanshan 2. University, Qinhuangdao, Hebei, ChinaAutomation Department of Shanxi University, Taiyuan, Shanxi 030006, China.;3. University, Qinhuangdao, Hebei, China;4. National Engineering Research Center for Equipment and Technology of Cold Strip Rolling, Qinhuangdao, Hebei, China |
| |
| Abstract: | A decentralized prescribed performance adaptive tracking control problem is investigated for Markovian jump uncertain nonlinear interconnected large‐scale systems. The considered interconnected large‐scale systems contain unknown nonlinear uncertainties, unknown control gains, actuator saturation, and Markovian jump signals, and the Markovian jump subsystems are in the form of triangular structure. First, by defining a novel state transformation with the performance function, the prescribed performance control problem is transformed to stabilization problem. Then, introducing an intermediate control signal into the control design, employing neural network to approximate the unknown composite nonlinear function, and based on the framework of the backstepping control design and adaptive estimation method, a corresponding decentralized prescribed performance adaptive tracking controller is designed. It is proved that all the signals in the closed‐loop system are bounded, and the prescribed tracking performances are guaranteed. A numerical example is provided to illustrate the effectiveness of the proposed control strategy. Copyright © 2016 John Wiley & Sons, Ltd. |
| |
| Keywords: | adaptive control prescribed performance control unknown control gain input saturation strict‐feedback Markovian jump nonlinear systems |
|
|
