Decentralized MRAC for large-scale interconnected systems with time-varying delays and applications to chemical reactor systems

2012 ◽  
Vol 22 (10) ◽  
pp. 1985-1996 ◽  
Author(s):  
Chang-Chun Hua ◽  
Jing Leng ◽  
Xin-Ping Guan
Keyword(s):  
Large Scale ◽  
Chemical Reactor ◽  
Interconnected Systems ◽  
Time Varying

Robust Decentralized Adaptive Control for Interconnected Systems With Time Delays

2005 ◽  
Vol 127 (4) ◽  
pp. 656-662 ◽  
Author(s):  
Changchun Hua ◽  
Xinping Guan ◽  
Peng Shi
Keyword(s):  
Time Delays ◽  
Large Scale ◽  
Robust Stabilization ◽  
Interconnected Systems ◽  
Multiple Time ◽  
Time Varying ◽  
Nonlinear Functions ◽  
Feedback Controllers ◽  
Large Scale Systems ◽  
Closed Loop Systems

The problem of robust stabilization for a class of time-varying nonlinear large-scale systems subject to multiple time-varying delays in the interconnections is considered. The interconnections satisfy the match condition, and are bounded by nonlinear functions that may contain a high-order polynomial with a time delay. Without the knowledge of these bounds, we present adaptive state feedback controllers that are continuous and independent of time delays. Based on the Lyapunov stability theorem, we prove that the controllers can render the closed loop systems uniformly ultimately bounded stable. We also apply the result to constructing adaptive feedback controllers to stabilize a class of interconnected systems whose nominal systems are linear. Finally, several examples are given to show the potential of the proposed techniques.

scholarly journals New Approach on Robust and Reliable Decentralized H∞ Tracking Control for Fuzzy Interconnected Systems with Time-Varying Delay

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Xinrui Liu ◽  
Qiuye Sun ◽  
Xinming Hou
Keyword(s):  
Tracking Control ◽  
Large Scale ◽  
Direct Method ◽  
Descriptor Systems ◽  
Interconnected Systems ◽  
Linear Matrix ◽  
Time Varying ◽  
Time Varying Delay ◽  
Actuator Failures ◽  
Varying Delay

This paper investigates the robust and reliable decentralized H∞ tracking control issue for the fuzzy large-scale interconnected systems with time-varying delay, which are composed of a number of T-S fuzzy subsystems with interconnections. Firstly, the ordinary fuzzy interconnected systems are equivalently transformed to the fuzzy descriptor systems; then, according to the Lyapunov direct method and the decentralized control theory of large-scale interconnected systems, the new linear matrix inequalities- (LMIs-) based conditions with some free variables are derived to guarantee the H∞ tracking performance not only when all control components are operating well, but also in the presence of some possible actuator failures. Moreover, there is no need for the precise failure parameters of the actuators, rather than the lower and upper bound. Finally, two simulation examples are provided to illustrate the effectiveness of the proposed method.

scholarly journals Adaptive Decentralized Output Feedback Tracking Control for Large-Scale Interconnected Systems with Time-Varying Output Constraints

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Min Wan ◽  
Yanxia Yin
Keyword(s):  
Output Feedback ◽  
Large Scale ◽  
Dynamic Surface Control ◽  
Learning Technologies ◽  
Interconnected Systems ◽  
Time Varying ◽  
Dynamic Surface ◽  
Control Scheme ◽  
Output Constraints ◽  
Two Parameters

This paper investigates a novel adaptive output feedback decentralized control scheme for nonstrict feedback large-scale interconnected systems with time-varying constraints. A decentralized linear state observer is designed to estimate the unmeasurable states of subsystems. Time-varying barrier Lyapunov functions are designed to ensure outputs are not violating constraints. A variable separation approach is applied to deal with the nonstrict feedback problem. Moreover, dynamic surface control and minimal parameter learning technologies are adopted to reduce the computation burden, and there are only two parameters for every subsystem to be updated online. The proof of stability is obtained by the Lyapunov method. Finally, simulation results are given to show the effectiveness of the proposed control scheme.

Control of interconnected systems with sensor delay based on decentralized adaptive neural dynamic surface method

2020 ◽  
pp. 095965182096652
Author(s):  
Barmak Beigzadehnoe ◽  
Zahra Rahmani ◽  
Alireza Khosravi ◽  
Behrooz Rezaie
Keyword(s):  
Neural Network ◽  
Large Scale ◽  
Chemical Reactor ◽  
Interconnected Systems ◽  
Linear Matrix ◽  
Dynamic Surface ◽  
Control Laws ◽  
Surface Design ◽  
Pendulum System ◽  
Inverted Pendulum System

In this article, an adaptive neural network is proposed for the tracking control problem of unknown nonlinear interconnected systems with inaccessible states and sensor delays based on dynamic surface strategy. The system has unknown nonlinearities and immeasurable states. Thus, a neural network state observer based on delayed outputs of subsystems is applied. The main difficulty in obtaining local observers’ gains is that undelayed outputs are not available. As a result, by utilizing proper Lyapunov–Krasovskii functionals in dynamic surface design procedures, the gains of local observers are given in terms of linear matrix inequalities. Then, appropriate changes in coordinates are defined using delayed outputs, observed states, and filtered virtual controls for the purpose of designing dynamic surface controllers. Subsequently, proper Lyapunov–Krasovskii functionals are introduced to deal with sensor delays and obtain control laws and stability criteria. Furthermore, the proposed decentralized control scheme can suitably conquer the decentralized tracking problem of unknown large-scale systems with sensor delays and guarantee that all the signals in the closed-loop interconnected systems be uniformly ultimately bounded. Finally, to show the effectiveness and efficiency of the proposed approach, the theoretic achievements are employed to design a controller for a double-inverted pendulum system and a cascade chemical reactor system.

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