scholarly journals An ABC Optimized Adaptive Fuzzy Sliding Mode Control Strategy for Full Vehicle Active Suspension System

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.

2018 ◽  
Vol 61 ◽  
pp. 00007
Author(s):  
Ibrahim Farouk Bouguenna ◽  
Ahmed Azaiz ◽  
Ahmed Tahour ◽  
Ahmed Larbaoui

In this paper a neuro-fuzzy-sliding mode control (NFSMC) with extended state observer (ESO) technique; is designed to guarantee the traction of an electric vehicle with two distinct permanent magnet synchronous motor (PMSM). Each PMSM systems (source-convertermotor) are attached to an electronic differential (ED), in order to adjust the senses of direction of the vehicle, and sustain a stable speed by adapting the difference in velocity of each motor-wheel according to the direction in the case of a turn. Two types of controllers are employed by a hybrid control scheme to assure the control and the performance of the vehicle. This hybrid control scheme guarantees the stability of the vehicle by ED, reduces the chattering phenomena in the PMSM electric motor, and improves the disturbance rejection ability which employs tow types of controllers. The neuro-fuzzy sliding mode control on the direct current loop and ESO controller on the speed loop, and the quadratic current loop; taking into account the dynamic of the vehicle. Simulation runs under Matlab/Simulink to assess the efficiency, and strength of the recommended control method on the closed loop system.


2011 ◽  
Vol 71-78 ◽  
pp. 4309-4312 ◽  
Author(s):  
Wen Da Zheng ◽  
Gang Liu ◽  
Jie Yang ◽  
Hong Qing Hou ◽  
Ming Hao Wang

This paper presents a FBFN-based (Fuzzy Basis Function Networks) adaptive sliding mode control algorithm for nonlinear dynamic systems. Firstly, we designed an perfect control law according to the nominal plant. However, there always exists discrepancy between nominal and actual mode, and the FBFN was applied to approximate the uncertainty. After that, the adaptive law was designed to update the parameters of FBFN to alleviate the approximating errors. Based on the theory of Lyapunov stability, the stability of the adaptive controller was given with a sufficient condition. Simulation example was also given to illustrate the effectiveness of the method.


2012 ◽  
Vol 468-471 ◽  
pp. 704-707
Author(s):  
Sheng Bin Hu ◽  
Wen Hua Lu ◽  
Zhi Yi Chen ◽  
Lei Lei ◽  
Yi Xuan Zhang

An adaptive Double Fuzzy Sliding Mode Control scheme for attitude control of Flapping Wing Micro Aerial Vehicle is proposed in this paper. Based on the feedback linearization technique, a sliding mode controller is designed. To faster response speed, a fuzzy controller is designed to adaptively tune the slope of sliding mode surface. To reduce the chattering, another fuzzy controller is designed to adaptively tune the switch part of sliding mode control. The system stability is proved by Lyapunov principle. Simulation results show that the proposed control scheme is effective.


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.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wende Zhao ◽  
Decheng Wang ◽  
Zhenzhong Chu ◽  
Mingjun Zhang

This paper investigates the control problem of the buoyancy regulation system for autonomous underwater vehicle (AUV). There are some problems to be considered in the oil-water conversion-based buoyancy regulation system, including the external seawater pressure, the pressure fluctuations, and the slow switching speed of the ball valve. The control accuracy of the buoyancy regulation under the traditional PID controller cannot meet the requirements of the project. In this paper, a fuzzy sliding mode control scheme is developed for the buoyancy regulation system to solve the abovementioned problems. At first, a mathematical model of the buoyancy regulation system is established, and the stability of the system is analyzed. Then, the sliding mode control algorithm is combined with the fuzzy system to improve the control accuracy. Finally, the pool-experiment results on a prototype show that the developed control scheme can meet the requirements of the control accuracy for the buoyancy regulation system.


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