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.

scholarly journals Adaptive Dynamic Surface Decentralized Output Feedback Control for Switched Nonstrict Feedback Large-Scale Systems with Unknown Dead Zones

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Min Wan ◽  
Shanshan Huang
Keyword(s):  
Output Feedback ◽  
Large Scale ◽  
Dead Zone ◽  
Output Feedback Control ◽  
Dynamic Surface Control ◽  
Learning Technology ◽  
Dynamic Surface ◽  
Large Scale Systems ◽  
Dead Zones ◽  
Control Scheme

This paper investigates a novel adaptive output feedback decentralized control scheme for switched nonstrict feedback large-scale systems with unknown dead zones. A decentralized linear state observer is designed to estimate the unmeasurable states of subsystems. The dead zone inverse technique is used to compensate the effect of the unknown dead zone. A variable separation approach is applied to deal with the nonstrict feedback problem. Moreover, dynamic surface control and minimal parameter learning technology are adopted to reduce the computation burden. The proof of stability and the arbitrary switching are obtained by the common Lyapunov method. Finally, simulation results are given to show the effectiveness of the proposed control scheme.

Dynamic output feedback control for nonlinear large-scale interconnected systems

2020 ◽  
Vol 39 (4) ◽  
pp. 801-821
Author(s):  
Ezzeddine Touti ◽  
Ali Sghaier Tlili ◽  
Muhannad Almutiry
Keyword(s):  
Decentralized Control ◽  
Output Feedback ◽  
Large Scale ◽  
Optimization Problem ◽  
Lyapunov Theory ◽  
Interconnected Systems ◽  
Dynamic Output Feedback ◽  
Content Type ◽  
Dynamic Output ◽  
Control Scheme

Purpose This paper aims to focus on the design of a decentralized observation and control method for a class of large-scale systems characterized by nonlinear interconnected functions that are assumed to be uncertain but quadratically bounded. Design/methodology/approach Sufficient conditions, under which the designed control scheme can achieve the asymptotic stabilization of the augmented system, are developed within the Lyapunov theory in the framework of linear matrix inequalities (LMIs). Findings The derived LMIs are formulated under the form of an optimization problem whose resolution allows the concurrent computation of the decentralized control and observation gains and the maximization of the nonlinearity coverage tolerated by the system without becoming unstable. The reliable performances of the designed control scheme, compared to a distinguished decentralized guaranteed cost control strategy issued from the literature, are demonstrated by numerical simulations on an extensive application of a three-generator infinite bus power system. Originality/value The developed optimization problem subject to LMI constraints is efficiently solved by a one-step procedure to analyze the asymptotic stability and to synthesize all the control and observation parameters. Therefore, such a procedure enables to cope with the conservatism and suboptimal solutions procreated by optimization problems based on iterative algorithms with multi-step procedures usually used in the problem of dynamic output feedback decentralized control of nonlinear interconnected systems.

scholarly journals Adaptive output feedback control for a class of uncertain non-strict feedback systems with asymmetric time-varying output constraints

2020 ◽  
Vol 12 (9) ◽  
pp. 168781402095882
Author(s):  
Min Wan ◽  
Shanshan Huang
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Tracking Error ◽  
Output Feedback Control ◽  
Time Varying ◽  
Dynamic Surface ◽  
Adaptive Output Feedback Control ◽  
Output Constraints ◽  
Fuzzy State ◽  
Strict Feedback

This study investigated a novel adaptive output feedback control scheme for non-strict feedback nonlinear systems with uncertainties, disturbances, and asymmetric time-varying output constraints. Because that the states of the system are unmeasurable, we used an adaptive fuzzy state observer to obtain the estimated values of the states. To make the output and tracking error satisfy their asymmetric time-varying constraints, an asymmetric time-varying barrier Lyapunov function was adopted. To overcome the “explosion of complexity” problem, we also adopted the dynamic surface control technology. The stability of the closed-loop system was proved by the Lyapunov method, and we give two simulation examples to show the effectiveness of the proposed control method.

scholarly journals Fuzzy State Observer-Based Adaptive Dynamic Surface Control of Nonlinear Systems with Time-Varying Output Constraints

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Min Wan ◽  
Qingyou Liu ◽  
Jiawei Zheng ◽  
Jiaru Song
Keyword(s):  
Nonlinear Systems ◽  
Dynamic Surface Control ◽  
State Observer ◽  
Time Varying ◽  
Dynamic Surface ◽  
Control Approach ◽  
Surface Control ◽  
Output Constraints ◽  
Fuzzy State ◽  
Fuzzy State Observer

In this paper, a new fuzzy dynamic surface control approach based on a state observer is proposed for uncertain nonlinear systems with time-varying output constraints and external disturbances. An adaptive fuzzy state observer is used to estimate the states that cannot be measured in the systems. In our method, a time-varying Barrier Lyapunov Function (BLF) is used to ensure that the output does not violate time-varying constraints. In addition, dynamic surface control (DSC) technology is applied to overcome the problem of “explosion of complexity” in a backstepping control. Finally, the stability and signal boundedness of the system are confirmed by the Lyapunov method. The simulation results show the effectiveness and correctness of the proposed method.

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