Fuzzy Sliding Mode Control for Active Suspension System with Proportional Differential Sliding Mode Observer

2018 ◽  
Vol 21 (1) ◽  
pp. 264-276 ◽  
Author(s):  
Bin Lin ◽  
Xiaoyu Su ◽  
Xiaohang Li
2021 ◽  
Vol 11 (22) ◽  
pp. 10925
Author(s):  
Gang Li ◽  
Zhiyong Ruan ◽  
Ruiheng Gu ◽  
Guoliang Hu

In order to reduce vehicle vibration during driving conditions, a fuzzy sliding mode control strategy (FSMC) for semi-active air suspension based on the magnetorheological (MR) damper is proposed. The MR damper used in the semi-active air suspension system was tested and analyzed. Based on the experimental data, the genetic algorithm was used to identify the parameters of the improved hyperbolic tangent model, which was derived for the MR damper. At the same time, an adaptive neuro fuzzy inference system (ANFIS) was used to build the reverse model of the MR damper. The model of a quarter vehicle semi-active air suspension system equipped with a MR damper was established. Aiming at the uncertainty of the air suspension system, fuzzy control was used to adjust the boundary layer of the sliding mode control, which can effectively suppress the influence of chattering on the control accuracy and ensure system stability. Taking random road excitation and impact road excitation as the input signal, the simulation analysis of passive air suspension, semi-active air suspension based on SMC and FSMC was carried out, respectively. The results show that the semi-active air suspension based on FSMC has better vibration attenuating performance and ride comfort.


2021 ◽  
Vol 17 (2) ◽  
pp. 151-165
Author(s):  
Atheel Abdul Zahra ◽  
Turki Abdalla

This work presents a Fuzzy based adaptive Sliding Mode Control scheme to deal with the control problem of full vehicle active suspension system and take into consideration the nonlinearities of the spring and damper, unmodeled dynamics as well as external disturbances. The control law of fuzzy-based Adaptive Sliding Mode Control scheme will update the parameters of fuzzy sliding mode control by using the stability analysis of Lyapunov criteria such that the convergence infinite time and the stability of the closed-loop is ensured. The proposed control scheme consists of four similar subsystems used for the four sides of the vehicle. The sub-control scheme contains two loops, the outer loop is built using a sliding mode controller with a fuzzy estimator to approximate and estimate the unknown parameters in the system. In the inner loop, a controller of type Fractional Order PID (FOPID) is utilized to create the required actuator force. All parameters in the four sub-control schemes are optimized utilizing Artificial Bee Colony (ABC) algorithm in order to improve the performance. The results indicate the effectiveness and good achievement of the proposed controller in providing the best ability to limit the vibration with good robustness properties in comparison with passive suspension system and using sliding mode control method. The controlled suspension system shows excellent results when it was tested with and without typical breaking and bending torques.


2021 ◽  
Vol 23 (5) ◽  
pp. 409-415
Author(s):  
Idriss Baba Arbi ◽  
Abdelkrim Allag

This paper presents an implementation of Fuzzy Sliding Mode Control for Sensorless Direct Torque Control (DTC) of a Permanent Magnets Synchronous Machine as a combination between the known performances of direct torque control on the one hand and the robustness of sliding mode control on the other hand. The fuzzy controller is introduced to reduce the effect of chattering phenomenon which is the major disadvantage of sliding mode control technique. The proposed controller is used to replace the conventional PI angular speed controller that generates the electromagnetic reference torque for DTC, in order to improve the dynamic and the permanent behaviors of the angular speed control response as well the electromagnetic torque. The proposed control technique is implemented without using speed or position sensors, where a Full Order Sliding Mode Observer is used. It is shown that the proposed control technique has given improved simulation results with different speed ranges and different load values.


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