scholarly journals Adaptive Control of MEMS Gyroscope Based on T-S Fuzzy Model

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Yunmei Fang ◽  
Shitao Wang ◽  
Juntao Fei ◽  
Mingang Hua
Keyword(s):  
Nonlinear Model ◽  
Reference Model ◽  
Fuzzy Model ◽  
Lyapunov Theory ◽  
Mems Gyroscope ◽  
Adaptive Law ◽  
Control Scheme ◽  
Estimation Scheme ◽  
Linear State ◽  
Takagi Sugeno

A multi-input multioutput (MIMO) Takagi-Sugeno (T-S) fuzzy model is built on the basis of a nonlinear model of MEMS gyroscope. A reference model is adjusted so that a local linear state feedback controller could be designed for each T-S fuzzy submodel based on a parallel distributed compensation (PDC) method. A parameter estimation scheme for updating the parameters of the T-S fuzzy models is designed and analyzed based on the Lyapunov theory. A new adaptive law can be selected to be the former adaptive law plus a nonnegative in variable to guarantee that the derivative of the Lyapunov function is smaller than zero. The controller output is implemented on the nonlinear model and T-S fuzzy model, respectively, for the purpose of comparison. Numerical simulations are investigated to verify the effectiveness of the proposed control scheme and the correctness of the T-S fuzzy model.

scholarly journals Nonlinear Model Following Control via Takagi-Sugeno Fuzzy Model

1999 ◽  
Vol 3 (2) ◽  
pp. 68-74 ◽  
Author(s):  
Tadanari Taniguchi ◽  
◽  
Kazuo Tanaka
Keyword(s):  
Nonlinear Model ◽  
Fuzzy Controller ◽  
Reference Model ◽  
Fuzzy Model ◽  
Feedback System ◽  
Linear Matrix ◽  
Model Following Control ◽  
Model Following ◽  
Special Cases ◽  
Takagi Sugeno

This paper presents a unified approach toward regulation and servocontrol problems as special cases of a nonlinear model following control via the Takagi-Sugeno fuzzy model. New parallel distributed compensation (PDC) is presented for realizing a nonlinear model following control. The new PDC fuzzy controller mirrors the structures of two Takagi-Sugeno fuzzy models representing a nonlinear system and nonlinear reference model. First, we derive linear matrix inequality (LMI) conditions to linearize the error system between the feedback system and the nonlinear reference model. A controller is designed using LMI conditions. Design examples verify the usefulness of nonlinear model following control.

Fuzzy Observer Design for a Class of Uncertain Nonlinear System

2015 ◽  
Vol 740 ◽  
pp. 257-260
Author(s):  
Xian Jia Feng ◽  
Shu Li Guo ◽  
Li Na Han
Keyword(s):  
Nonlinear System ◽  
Magnetic Levitation ◽  
Fuzzy Model ◽  
Observer Design ◽  
Uncertain Nonlinear System ◽  
Adaptive Law ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
Takagi Sugeno ◽  
Fuzzy State

In this paper, a fuzzy state observer with an appropriate adaptive law is developed for a class of uncertain nonlinear system. The uncertain nonlinear system is represented by Takagi-Sugeno (T-S) fuzzy model, and the adaptive law is derived based on Lyapunov synthesis approach. It is shown that under appropriate assumptions, the state error between plant system state and desired linear model state converges to zero as time increases. The results of numerical simulation and the experiment on the magnetic levitation system show the effectiveness of this approach.

scholarly journals Observer-Based Fuzzy Control for Memristive Circuit Systems

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Qian Ye ◽  
Xuyang Lou
Keyword(s):  
Fuzzy Control ◽  
Chaotic System ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Chaotic Circuit ◽  
Control Scheme ◽  
Simulation Results ◽  
Memristive Circuit ◽  
Takagi Sugeno

This paper proposes an observer-based fuzzy control scheme for a class of memristive chaotic circuit systems. First, the Takagi-Sugeno fuzzy model is adopted to reconstruct the nonlinear chaotic circuit system. Next, based on the proposed fuzzy model, an observer-based fuzzy controller is developed to estimate the states and stabilize the origin. Third, the results are extended to explore the L∞-gain observer-based fuzzy control for the chaotic system with disturbances. Finally, simulation results are also addressed to show the effectiveness of the proposed control scheme.

AN OPTIMAL REAL-TIME TRAJECTORY TRACKING CONTROL DESIGN FOR PENDUBOT VIA TAKAGI-SUGENO FUZZY MODEL

2005 ◽  
Vol 29 (2) ◽  
pp. 247-265
Author(s):  
Zhen Cai ◽  
Chun-Yi Su
Keyword(s):  
Real Time ◽  
Trajectory Tracking ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Trajectory Tracking Control ◽  
Linear Regulator ◽  
Control Scheme ◽  
The Stability ◽  
Takagi Sugeno ◽  
Underactuated Robot

In this paper, an optimal fuzzy control scheme is presented to achieve trajectory tracking for the Pendubot, an underactuated robot by combining linear optimal control theory and linear regulator theory with the Takagi-Sugeno fuzzy methodology. The stability of the entire closed-loop fuzzy system is analyzed by the designed optimal fuzzy controller. The real-time application of the proposed algorithm on the Pendubot is also addressed.

scholarly journals Control Theory Application for Swing Up and Stabilisation of Rotating Inverted Pendulum

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1491
Author(s):  
Xhevahir Bajrami ◽  
Arbnor Pajaziti ◽  
Ramë Likaj ◽  
Ahmet Shala ◽  
Rinor Berisha ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Inverted Pendulum ◽  
Reference Model ◽  
Sliding Mode ◽  
Upright Position ◽  
Linear Range ◽  
Lyapunov Theory ◽  
System Control ◽  
Mode Control ◽  
Control Scheme

This paper introduces a new scheme for sliding mode control using symmetry principles for a rotating inverted pendulum, with the possibility of extension of this control scheme to other dynamic systems. This was proven for swing up and stabilisation control problems via the new sliding mode control scheme using both simulations and experiments of rotary inverted pendulum (RIP) underactuated systems. According to the Lyapunov theory, a section of the pendulum was compensated with a scale error in the upright position, as the desired trajectory was followed by the pendulum arm section. As the RIP’s dynamic equations were nonlinearly complex and coupled, the complex internal dynamics made the task of controller design difficult. The system control for the pathway of the reference model of the rotational actuator with the application of the sliding mode technique for moving back and forth up the inverted pendulum’s structure, till the arm to reach the linear range round the vertical upright position, was created and tested in an existent device. The stabilisation scheme was switched on in the sliding mode as soon as the arm reached the linear range. A comparison of the stabilisation performance for the same rotating inverted pendulum as discussed by other authors revealed that the proposed controller was more flexible and reliable in terms of the swing up and stabilisation time.

Optimal Model Reference Control Scheme Design for Nonlinear Strict-Feedback Systems

2020 ◽  
Vol 38 (9A) ◽  
pp. 1342-1351
Author(s):  
Musadaq A. Hadi ◽  
Hazem I. Ali
Keyword(s):  
Reference Model ◽  
Feedback System ◽  
Optimization Method ◽  
Feedback Systems ◽  
Model Reference ◽  
Scheme Design ◽  
Model Reference Control ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Strict Feedback

In this paper, a new design of the model reference control scheme is proposed in a class of nonlinear strict-feedback system. First, the system is analyzed using Lyapunov stability analysis. Next, a model reference is used to improve system performance. Then, the Integral Square Error (ISE) is considered as a cost function to drive the error between the reference model and the system to zero. After that, a powerful metaheuristic optimization method is used to optimize the parameters of the proposed controller. Finally, the results show that the proposed controller can effectively compensate for the strictly-feedback nonlinear system with more desirable performance.

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.

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