Fuzzy constrained MPC output feedback controller design for nonlinear systems based on parameter-dependent Lyapunov function approach

2013 ◽  
Author(s):  
Hui-Wei Liu ◽  
Ke-Zhen Han ◽  
Xiao-Heng Chang
Keyword(s):  
Nonlinear Systems ◽  
Lyapunov Function ◽  
Output Feedback ◽  
Controller Design ◽  
Feedback Controller ◽  
Function Approach ◽  
Output Feedback Controller ◽  
Parameter Dependent

scholarly journals Output feedback controller design for polynomial linear parameter varying system via parameter-dependent Lyapunov functions

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401769032 ◽  
Author(s):  
Xiaobao Han ◽  
Zhenbao Liu ◽  
Huacong Li ◽  
Xianwei Liu
Keyword(s):  
Output Feedback ◽  
Optimization Problem ◽  
Controller Design ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Output Feedback Controller ◽  
Parameter Varying ◽  
Parameter Dependent

This article presents a new output feedback controller design method for polynomial linear parameter varying model with bounded parameter variation rate. Based on parameter-dependent Lyapunov function, the polynomial linear parameter varying system controller design is formulated into an optimization problem constrained by parameterized linear matrix inequalities. To solve this problem, first, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameter-dependent Lyapunov function, controller, and object coefficient matrices. Then, the control solving problem was reduced to a normal convex optimization problem with linear matrix inequalities constraint on a newly constructed convex polyhedron. Moreover, a parameter scheduling output feedback controller was achieved on the operating condition, which satisfies robust performance and dynamic performances. Finally, the feasibility and validity of the controller analysis and synthesis method are verified by the numerical simulation.

Adaptive output feedback control for a class of uncertain stochastic nonlinear systems

2021 ◽  
pp. 095965182110212
Author(s):  
Ce Liu ◽  
Junyong Zhai
Keyword(s):  
Nonlinear Systems ◽  
Output Feedback ◽  
Controller Design ◽  
Output Feedback Control ◽  
Feedback Controller ◽  
Stochastic Nonlinear Systems ◽  
Adding A Power Integrator ◽  
Output Feedback Controller ◽  
Barbalat’S Lemma ◽  
System States

This article concentrates on the output feedback controller design for a class of stochastic nonlinear systems with unknown homogeneous growth rates. First, a full-order observer is proposed coupling with a dynamic gain so as to obtain system state estimates. Then, an adaptive output feedback controller is put forward by the homogeneity theory and adding a power integrator technique. Combined with the stochastic Barbalat’s lemma, the signals of the closed-loop system are demonstrated to be bounded and all the system states are proved to converge to the origin in probability. Besides, the results are also expanded to the controller design of upper-triangular stochastic nonlinear system. Two simulation results indicate usefulness of the designed control algorithm.

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