Robust adaptive fuzzy controller with supervisory compensator for MEMS gyroscope sensor

Robotica ◽  
2015 ◽  
Vol 34 (10) ◽  
pp. 2330-2343 ◽  
Author(s):  
Yunmei Fang ◽  
Jian Zhou ◽  
Juntao Fei
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Adaptive Controller ◽  
State Variables ◽  
Inference System ◽  
Mems Gyroscope ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Robust Adaptive ◽  
Gyroscope Sensor

SUMMARYIn this paper, a robust adaptive fuzzy controller is proposed to improve the robustness and position tracking of a MEMS gyroscope sensor. The proposed controller is designed as an indirect adaptive fuzzy controller with a supervisory compensator. It incorporates a fuzzy inference system with an adaptive controller in a unified Lyapunov framework, which can approximate and compensate for the unknown system dynamics and nonlinearities in the MEMS gyroscope. The parameters of the membership functions in the fuzzy controller can be adjusted online based on the Lyapunov method. Moreover, a supervisory controller is employed to guarantee the asymptotic stability of the closed-loop system and boundedness of the state variables in the MEMS gyroscope model. Numerical simulations demonstrate the proposed robust adaptive fuzzy controller has satisfactory tracking performance and robustness in the presence of external disturbances.

Research of Robust Adaptive Fuzzy Control in Manipulator

2011 ◽  
Vol 317-319 ◽  
pp. 713-717
Author(s):  
Hong Lin Li ◽  
Peng Bing Zhao
Keyword(s):  
Fuzzy Control ◽  
Influencing Factors ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Random Disturbance ◽  
State Variables ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Load Variation ◽  
Robust Adaptive

There are friction characteristics, random disturbance, load variation and other nonlinear influencing factors in the multi-joint manipulator system generally. According to the problem that the traditional PID and fuzzy control are difficult to achieve rapid and high-precision control for this kind of system, a kind of robust adaptive fuzzy controller was designed based on fuzzy compensation under the circumstances that the fuzzy information can be known and all the state variables can be measured. Simultaneously, in order to reduce the computational load of fuzzy approximation and improve the efficiency of mathematical operation, a method that distinguishing different disturbance compensatory terms and approximating each of them respectively was adopted. The simulation results show that the robust adaptive fuzzy controller based on fuzzy compensation can restrain friction, disturbance, load variation and other nonlinear influencing factors.

scholarly journals A Heating Controller Designing Based on Living Space Heating Dynamic’s Model Approach in a Smart Building

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 998
Author(s):  
Roozbeh Sadeghian Broujeny ◽  
Kurosh Madani ◽  
Abdennasser Chebira ◽  
Veronique Amarger ◽  
Laurent Hurtard
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Time Series Prediction ◽  
Adaptive Controller ◽  
Inference System ◽  
Diverse Range ◽  
Smart Building ◽  
Living Space ◽  
Soft Computing Techniques

Most already advanced developed heating control systems remain either in a prototype state (because of their relatively complex implementation requirements) or require very specific technologies not implementable in most existing buildings. On the other hand, the above-mentioned analysis has also pointed out that most smart building energy management systems deploy quite very basic heating control strategies limited to quite simplistic predesigned use-case scenarios. In the present paper, we propose a heating control strategy taking advantage of the overall identification of the living space by taking advantage of the consideration of the living space users’ presence as additional thermal sources. To handle this, an adaptive controller for the operation of heating transmitters on the basis of soft computing techniques by taking into account the diverse range of occupants in the heating chain is introduced. The strategy of the controller is constructed on a basis of the modeling heating dynamics of living spaces by considering occupants as an additional heating source. The proposed approach for modeling the heating dynamics of living spaces is on the basis of time series prediction by a multilayer perceptron neural network, and the controlling strategy regarding the heating controller takes advantage of a Fuzzy Inference System with the Takagi-Sugeno model. The proposed approach has been implemented for facing the dynamic heating conduct of a real five-floor building’s living spaces located at Senart Campus of University Paris-Est Créteil, taking into account the occupants of spaces in the control chain. The obtained results assessing the efficiency and adaptive functionality of the investigated fuzzy controller designed model-based approach are reported and discussed.

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.

Sign in / Sign up

Export Citation Format

Share Document