Decentralized robust adaptive fuzzy controller for large-scale nonlinear uncertain systems

2004 ◽  
Author(s):  
Chiang-Cheng Chiang ◽  
Wen-Hao Wang
Keyword(s):  
Uncertain Systems ◽  
Large Scale ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Nonlinear Uncertain Systems ◽  
Robust Adaptive

scholarly journals Observer-Based Robust Adaptive Fuzzy Control for MIMO Nonlinear Uncertain Systems with Delayed Output

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Chiang Cheng Chiang
Keyword(s):  
Nonlinear System ◽  
Fuzzy Control ◽  
Robust Stability ◽  
Uncertain Systems ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Controlled System ◽  
Adaptive Fuzzy ◽  
Nonlinear Uncertain Systems ◽  
Robust Adaptive

An observer-based robust adaptive fuzzy control scheme is presented to tackle the problem of the robust stability and the tracking control for a class of multiinput multioutput (MIMO) nonlinear uncertain systems with delayed output. Because the nonlinear system functions and the uncertainties of the controlled system including structural uncertainties are supposed to be unknown, fuzzy logic systems are utilized to approximate these nonlinear system functions and the upper bounded functions of the uncertainties. Moreover, the upper bound of uncertainties caused by these fuzzy modeling errors is also estimated. In addition, the state observer based on state variable filters is designed to estimate all states which are not available for measurement in the controlled system. By constructing an appropriate Lyapunov function and using strictly positive-real (SPR) stability theorem, the proposed robust adaptive fuzzy controller not only guarantees the robust stability of a class of multivariable nonlinear uncertain systems with delayed output but also maintains a good tracking performance. Finally, some simulation results are illustrated to verify the effectiveness of the proposed control approach.

scholarly journals Parameter tuning of robust adaptive fuzzy controller for 3D elliptical vibration-assisted cutting

2021 ◽  
Vol 12 (1) ◽  
pp. 433-442
Author(s):  
Yongsheng Du ◽  
Mingming Lu ◽  
Hao Wang ◽  
Jiakang Zhou ◽  
Jieqiong Lin
Keyword(s):  
Fuzzy Controller ◽  
Optimal Solution ◽  
Parameter Tuning ◽  
Precision Machining ◽  
Step Size ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Elliptical Vibration ◽  
Robust Adaptive ◽  
Control Accuracy

Abstract. Elliptical vibration cutting (EVC), as a precision machining technology, is used in many applications. In precision machining, control accuracy plays an essential role in improving the machinability of difficult-to-machine materials. To improve the control accuracy, dynamic and static characteristics of the system need to be tuned to obtain the optimal parameters. In this paper, we use a glowworm algorithm with an improved adaptive step size to tune the parameters of a robust adaptive fuzzy controller. We then obtain the optimal controller parameters through simulation. The optimal solution of the controller parameters is then applied to a 3D EVC system model for simulation and closed-loop testing experiments. The results indicate that a good agreement between the ideal curve and the tracking signal curve verifies the optimality of the controller parameters. Finally, under certain cutting conditions, the workpieces of three different materials are cut with two different cutting methods. The study revealed that the surface roughness value is reduced by 20 %–32 %, which further verifies the effectiveness of the optimal controller's parameters.

scholarly journals Design of Robust Adaptive Fuzzy Controller for a Class of Single-Input Single-Output (SISO) Uncertain Nonlinear Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Jieqiong Lin ◽  
Jiakang Zhou ◽  
Mingming Lu ◽  
Hao Wang ◽  
Allen Yi
Keyword(s):  
Fuzzy Controller ◽  
Elliptical Vibration Cutting ◽  
Single Input Single Output ◽  
Vibration Cutting ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Elliptical Vibration ◽  
Single Output ◽  
Single Input ◽  
Robust Adaptive

In order to solve the precision and stability control problems of nonlinear uncertain systems applied in machining systems, in this paper, a robust adaptive fuzzy control technique based on Dynamic Surface Control (DSC) method is proposed for the generalized single-input single-output (SISO) uncertain nonlinear system. A first-order low-pass filter is introduced in each step of the traditional robust control method to overcome the “calculation expansion” problem, and Takagi–Sugeno (T-S) fuzzy logic system is applied to approximate an uncertain nonlinear function of unknown structure in the system. The designed robust adaptive fuzzy controller is applied to the 3D elliptical vibration cutting (3D EVC) device system model, and the effectiveness of the controller design is verified by analysis of position tracking, speed tracking, and tracking error. The results of studies show that the robust adaptive fuzzy controller can effectively suppress the jitter problem of the three-dimensional elliptical vibration cutting device so that the control object can be stabilized quickly even if it has a little jitter at the beginning. It can be smoothed to move along the ideal displacement and velocity signals. It is verified that the designed controller has strong robust adaptability.

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