An adaptive fuzzy sliding-mode controller for servomechanism disturbance rejection

Shi, Huaitao; Huang, Kuo-See

doi:10.1109/41.937418

Cited by 22 publications

(5 citation statements)

References 26 publications

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“…Consequently, it is difficult to predict control performance in the event of changes to the system parameters. This led researchers to develop AFSMC [15], which combines the advantages of fuzzy control, sliding mode control, and adaptive control. In a control system with unknown parameters, analyzing the input and output data can further understanding of the control system in order to establish language rules.…”

Section: Adaptive Fuzzy Sliding Mode Controlmentioning

confidence: 99%

“…Using the chain rule, we can rewrite Equation (14) into (15) where c(e) is the direction of the control variable, and γ a is the learning rate parameter. When errors and error variations exist in the system, C i increases continually, which causes the system to diverge.…”

Section: Adaptive Fuzzy Sliding Mode Controlmentioning

confidence: 99%

“…This gives the AFSMC the functions of online learning and updating the defuzzification rule bank. For details on the design process and theory of AFSMC, please refer to [15]. In sliding model control, the sliding surface reaching condition is…”

Section: Adaptive Fuzzy Sliding Mode Controlmentioning

confidence: 99%

“…The controller designs are similar to those in [14]; however, we replace PD control with AFSMC control to handle the complex vibration behaviors found in actual flexible structures more effectively. please refer to [15]. Figure 4 presents the hybrid RC framework adopted in this study, where C1 and C2 respectively represent the AFSMC controller and the repetitive controller.…”

Section: Adaptive Fuzzy Sliding Mode Controlmentioning

confidence: 99%

“…Adaptive fuzzy sliding mode control (AFSMC) was used in the latter to deal with complex vibrations generated by the rotation of the thin flexible plate. This control method can effectively handle nonlinear systems with uncertain parameters and achieve the expected control performance [15][16][17]. To minimize the influence of the periodic disturbances caused by the periodic motions of the motor, we adopted a hybrid RC framework [13,14] to combine RC with AFSMC and enhance piezoelectric vibration-suppression control.…”

Section: Introductionmentioning

confidence: 99%

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Active Vibration Suppression of a Motor-Driven Piezoelectric Smart Structure Using Adaptive Fuzzy Sliding Mode Control and Repetitive Control

Lin

Jheng

2017

Applied Sciences

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Abstract:In this paper, we report on the use of piezoelectric sensors and actuators for the active suppression of vibrations associated with the motor-driven rotation of thin flexible plate held vertically. Motor-driven flexible structures are multi-input multi-output systems. The design of active vibration-suppression controllers for these systems is far more challenging than for flexible structures with a fixed end, due to the effects of coupling and nonlinear vibration behavior generated in structures with poor damping. To simplify the design of the controller and achieve satisfactory vibration suppression, we treated the coupling of vibrations caused by the rotary motion of the thin flexible plate as external disturbances and system uncertainties. We employed an adaptive fuzzy sliding mode control algorithm in the design of a single-input-single-output controller for the suppression of vibrations using piezoelectric sensors and actuators. We also used a repetitive control system to reduce periodic vibrations associated with the repetitive motions induced by the motor. Experimental results demonstrate that the hybrid intelligent control approach proposed in this study can suppress complex vibrations caused by modal excitation, coupling effects, and periodic external disturbances.

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Section: Adaptive Fuzzy Sliding Mode Controlmentioning

confidence: 99%

Section: Adaptive Fuzzy Sliding Mode Controlmentioning

confidence: 99%

Section: Adaptive Fuzzy Sliding Mode Controlmentioning

confidence: 99%

Section: Adaptive Fuzzy Sliding Mode Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Active Vibration Suppression of a Motor-Driven Piezoelectric Smart Structure Using Adaptive Fuzzy Sliding Mode Control and Repetitive Control

Lin

Jheng

2017

Applied Sciences

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Speed control of BLDCM based on compensated fuzzy neural network

Zhang

2014

The 26th Chinese Control and Decision Conference (2014 CCDC)

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Brushless DC motor (BLDCM) not only has good speed control performance of DC motor, but also has the advantages has a simple structure, reliable operation of AC servo-motor, thus it has found wide applications in many high performance servo systems. Because brushless DC motor servo system is a multivariate, nonlinear, strong-coupled time-varying system, traditional PID control does not meet the requirements of high precision control. Advanced control strategies, such as fuzzy control, neural network, variable structure control, adaptive control and so on are widely used in the servo system of brushless DC motor. Compensatory fuzzy neural network (CFFN) combined advantages of compensation logic and neural network, so using compensated fuzzy neural networks (CFNNC) to control brushless DC motor position servo system can increase tracking accuracy and response speed. . Abstract Aiming at the multivariable, nonlinearity, strong coupling, time-variable characteristics of speed control system of brushless DC motor( BLDCM ),the CFNNC algorithm is proposed to obtain high precision speed controlling . This algorithm combines compensative fuzzy logic and neural network, adjust the input and output of fuzzy membership functions, and optimize the fuzzy inference dynamically according to the logic compensation algorithm. The fault tolerance, stability and working speed of the network are improved greatly due to the introduction of fuzzy neuron. The simulation and experiment results of DSP -based control system prove that this method have rapid response and robustness , and its dynamic characteristic is much better than that of traditional PID controller.

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Fuzzy global sliding mode control for uncertain delay systems with actuator faults

Yang

et al. 2016

2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)

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An adaptive fuzzy sliding-mode controller for servomechanism disturbance rejection

Cited by 22 publications

References 26 publications

Active Vibration Suppression of a Motor-Driven Piezoelectric Smart Structure Using Adaptive Fuzzy Sliding Mode Control and Repetitive Control

Active Vibration Suppression of a Motor-Driven Piezoelectric Smart Structure Using Adaptive Fuzzy Sliding Mode Control and Repetitive Control

Speed control of BLDCM based on compensated fuzzy neural network

Fuzzy global sliding mode control for uncertain delay systems with actuator faults

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