scholarly journals Damping Force Tracking Control of MR Damper System Using a New Direct Adaptive Fuzzy Controller

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Xuan Phu Do ◽  
Kruti Shah ◽  
Seung-Bok Choi
Keyword(s):  
Vibration Control ◽  
Tracking Control ◽  
Fuzzy Controller ◽  
Tracking Error ◽  
Mr Damper ◽  
Control Performance ◽  
Damping Force ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Force Tracking

This paper presents a new direct adaptive fuzzy controller and its effectiveness is verified by investigating the damping force tracking control of magnetorheological (MR) fluid based damper (MR damper in short) system. In the formulation of the proposed controller, a model of interval type 2 fuzzy controller is combined with the direct adaptive control to achieve high performance in vibration control. In addition,H∞(Hinfinity) tracking technique is used in building a model of the direct adaptive fuzzy controller in which an enhanced iterative algorithm is combined with the fuzzy model. After establishing a closed-loop control structure to achieve high control performance, a cylindrical MR damper is adopted and damping force tracking results are obtained and discussed. In addition, in order to demonstrate the effectiveness of the proposed control strategy, two existing controllers are modified and tested for comparative work. It has been demonstrated from simulation and experiment that the proposed control scheme provides much better control performance in terms of damping force tracking error. This leads to excellent vibration control performance of the semiactive MR damper system associated with the proposed controller.

scholarly journals A New Switching Adaptive Fuzzy Controller with an Application to Vibration Control of a Vehicle Seat Suspension Subjected to Disturbances

2021 ◽  
Vol 11 (5) ◽  
pp. 2244
Author(s):  
Do Xuan Phu ◽  
Van Mien ◽  
Seung-Bok Choi
Keyword(s):  
Vibration Control ◽  
Fuzzy Controller ◽  
Mr Damper ◽  
Small Disturbance ◽  
Sliding Surface ◽  
Control Performance ◽  
External Disturbances ◽  
Adaptive Fuzzy Controller ◽  
Seat Suspension ◽  
Vehicle Seat

This paper proposes a new switching adaptive fuzzy controller and applies it to vibration control of a vehicle seat suspension equipped with a semi-active magnetorheological (MR) damper. The proposed control system consists of three functioned filters: (1) Filter 1: a model of interval type 2 fuzzy to compensate disturbances; (2) Filter 2: a ‘switching term’ to evaluate the magnitude of disturbance; and (3) Filter 3: a group of adaptation laws to enhance the robustness of control input. These filters play a role of powerful shields to improve control performance and guarantee the stability of the applied system subjected to external disturbances. After embedding a PID (proportional-integral-derivative) model into Riccati-like equation, main control parameters are updated based on the adaptation laws. The proposed controller is then synthesized in two different cases: high disturbance and small disturbance. For the high disturbance, a special type of sliding surface function, which relates to an exponential function and its t-norm, is used to increase the energy of control system. For the small disturbance, the energy from the modified t-norm of the sliding surface is neglected to reduce the energy consumption with maintaining the desired performance. To demonstrate the effectiveness of the proposed controller, a vehicle seat suspension installed with controllable MR damper is adopted to reflect the robustness against external disturbances corresponding to road excitations. It is validated from computer simulation that the proposed controller can provide better vibration control performance than other existing robust controllers showing excellent control stability with well-reduced displacement and velocity at the position of the seat.

Design of Adaptive Fuzzy Control for a Class of Networked Nonlinear Systems

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
Mohamed Hamdy ◽  
Sameh Abd-Elhaleem ◽  
M. A. Fkirin
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
External Disturbance ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Time Varying ◽  
Fuzzy Logic Systems ◽  
Packet Losses ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy

This paper presents an adaptive fuzzy controller for a class of unknown nonlinear systems over network. The network-induced delays can degrade the performance of the networked control systems (NCSs) and also can destabilize the system. Moreover, the seriousness of the delay problem is aggravated when packet losses occur during a transmission of data. The proposed controller uses a filtered tracking error to cope the time-varying network-induced delays. It is also robust enough to cope some packet losses in the system. Fuzzy logic systems (FLSs) are used to approximate the unknown nonlinear functions that appear in the tracking controller. Based on Lyapunov stability theory, the constructed controller is proved to be asymptotically stable. Stability of the adaptive fuzzy controller is guaranteed in the presence of bounded external disturbance, time-varying delays, and data packet dropouts. Simulated application of the inverted pendulum tracking illustrates the effectiveness of the proposed technique with comparative results.

scholarly journals Uncertain Fractional Order Chaotic Systems Tracking Design via Adaptive Hybrid Fuzzy Sliding Mode Control

2011 ◽  
Vol 6 (3) ◽  
pp. 418 ◽  
Author(s):  
Tsung-Chih Lin ◽  
Chia-Hao Kuo ◽  
Valentina E. Balas
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Chaotic Systems ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Tracking Error ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Mode Control ◽  
And Control

In this paper, in order to achieve tracking performance of uncertain fractional order chaotic systems an adaptive hybrid fuzzy controller is proposed. During the design procedure, a hybrid learning algorithm combining sliding mode control and Lyapunov stability criterion is adopted to tune the free parameters on line by output feedback control law and adaptive law. A weighting factor, which can be adjusted by the trade-off between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive fuzzy controller and direct adaptive fuzzy controller. To confirm effectiveness of the proposed control scheme, the fractional order chaotic response system is fully illustrated to track the trajectory generated from the fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control structure is more flexible during the design process.

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