scholarly journals Robust Wheel Slip for Vehicle Anti-lock Braking System with Fuzzy Sliding Mode Controller (FSMC)

2020 ◽  
Vol 10 (5) ◽  
pp. 6368-6373
Author(s):  
S. Latreche ◽  
S. Benaggoune
Keyword(s):  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Closed Loop System ◽  
Wheel Slip ◽  
Ground Vehicle ◽  
Strongly Nonlinear ◽  
Braking System ◽  
Fuzzy Sliding Mode ◽  
The Stability ◽  
New Strategies

Anti-lock Braking System (ABS) is used in automobiles to prevent slipping and locking of wheels after the brakes are applied. Its control is a rather complicated problem due to its strongly nonlinear and uncertain characteristics. The aim of this paper is to investigate the wheel slip control of the ground vehicle, comprising two new strategies. The first strategy is the Sliding Mode Controller (SMC) and the second one is the Fuzzy Sliding Mode Controller (FSMC), which is a combination of fuzzy logic and sliding mode, to ensure the stability of the closed-loop system and remove the chattering phenomenon introduced by classical sliding mode control. The obtained simulation results reveal the efficiency of the proposed technique for various initial road conditions.

A Grey Sliding Mode Controller Design for Antilock Braking System

2007 ◽  
Author(s):  
Yesim Oniz ◽  
Erdal Kayacan ◽  
Okyay Kaynak
Keyword(s):  
Controller Design ◽  
Sliding Mode ◽  
Grey System Theory ◽  
Sliding Mode Controller ◽  
Control Methods ◽  
Grey System ◽  
Wheel Slip ◽  
Braking System ◽  
Antilock Braking System ◽  
Antilock Braking

The main control objective of an Antilock Braking System (ABS) is to increase the tractive forces between wheel and road surface by keeping the wheel slip at the peak value of μ – λ curve. Conventionally, it is assumed that optimal wheel slip is constant. In this paper, a grey sliding mode controller is proposed to regulate optimal wheel slip depending on the vehicle forward velocity. ABS exhibits strongly nonlinear and uncertain characteristics. To overcome these difficulties, robust control methods should be employed. The concept of grey system theory, which has a certain prediction capability, offers an alternative approach to conventional control methods. The proposed controller anticipates the upcoming values of wheel slip and optimal wheel slip, and takes the necessary action to keep wheel slip at the desired value. The control algorithm is applied to a quarter vehicle model, and it is verified through simulations indicating fast convergence and good performance of the designed controller.

A study on an anti-lock braking system controller and rear-wheel controller to enhance vehicle lateral stability

2007 ◽  
Vol 221 (7) ◽  
pp. 777-787 ◽  
Author(s):  
Jeonghoon Song ◽  
Heungseob Kim ◽  
Kwangsuck Boo
Keyword(s):  
Sliding Mode ◽  
Dynamic Performance ◽  
Rear Wheel ◽  
Slip Angle ◽  
Lateral Stability ◽  
Motion Controller ◽  
Wheel Slip ◽  
Stopping Distance ◽  
Braking System ◽  
The Stability

This paper presents a mathematical vehicle model that is designed to analyse and improve the dynamic performance of a vehicle. A wheel slip controller for anti-lock braking system (ABS) brakes is formulated using a sliding mode controller and a proportional-integral-derivative (PID) controller for rear wheel steering is also designed to enhance the stability, steerability, and driveability of the vehicle during transient manoeuvres. The braking and steering performances of controllers are evaluated for various driving conditions, such as straight and J-turn manoeuvres. The simulation results show that the proposed full car model is sufficient to predict vehicle responses accurately. The developed ABS reduces the stopping distance and increases the longitudinal and lateral stability of both two-and four-wheel steering vehicles. The results also demonstrate that the use of a rear wheel controller as a yaw motion controller can increase its lateral stability and reduce the slip angle at high speeds.

scholarly journals GA-Based Fuzzy Sliding Mode Controller for Nonlinear Systems

2008 ◽  
Vol 2008 ◽  
pp. 1-16 ◽  
Author(s):  
P. C. Chen ◽  
C. W. Chen ◽  
W. L. Chiang
Keyword(s):  
Nonlinear System ◽  
Nonlinear Systems ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Reference Trajectory ◽  
Parameter Vector ◽  
Adaptive Fuzzy ◽  
Initial Values ◽  
Fuzzy Sliding Mode ◽  
The Stability

Generally, the greatest difficulty encountered when designing a fuzzy sliding mode controller (FSMC) or an adaptive fuzzy sliding mode controller (AFSMC) capable of rapidly and efficiently controlling complex and nonlinear systems is how to select the most appropriate initial values for the parameter vector. In this paper, we describe a method of stability analysis for a GA-based reference adaptive fuzzy sliding model controller capable of handling these types of problems for a nonlinear system. First, we approximate and describe an uncertain and nonlinear plant for the tracking of a reference trajectory via a fuzzy model incorporating fuzzy logic control rules. Next, the initial values of the consequent parameter vector are decided via a genetic algorithm. After this, an adaptive fuzzy sliding model controller, designed to simultaneously stabilize and control the system, is derived. The stability of the nonlinear system is ensured by the derivation of the stability criterion based uponLyapunov's direct method. Finally, an example, a numerical simulation, is provided to demonstrate the control methodology.

Fuzzy Sliding Mode Control for Semi-Active Suspension System

2011 ◽  
Vol 268-270 ◽  
pp. 1595-1600
Author(s):  
Jing Jun Zhang ◽  
Wei Sha Han ◽  
Rui Zhen Gao
Keyword(s):  
Fuzzy Controller ◽  
Sliding Mode ◽  
Active Suspension ◽  
Sliding Mode Controller ◽  
Mode Switch ◽  
Fuzzy Sliding Mode Control ◽  
Absolute Value ◽  
Reference Models ◽  
Fuzzy Sliding Mode ◽  
The Stability

In Matlab/Simulink software semi-active suspension dynamic model of a quarter car is established and a sliding mode controller and a fuzzy sliding mode controller are designed. The fuzzy controller inputs are sliding mode switch function and its derivatives, and the output of absolute value is the sliding mode controller parameters. This fuzzy sliding mode controller chooses sliding mode controller and Skyhook as reference models and the simulation result shows that the stability of performance of the fuzzy sliding mode controller can effectively improve the driving smoothness and safety.

Bond graph model-based evaluation of a sliding mode controller for a combined regenerative and antilock braking system

2011 ◽  
Vol 225 (7) ◽  
pp. 918-934 ◽  
Author(s):  
T K Bera ◽  
K Bhattacharya ◽  
A K Samantaray
Keyword(s):  
Load Transfer ◽  
Sliding Mode ◽  
Graph Model ◽  
Bond Graph ◽  
Sliding Mode Controller ◽  
Wheel Slip ◽  
Control Laws ◽  
Braking System ◽  
Antilock Braking System ◽  
Antilock Braking

Combined regenerative and antilock braking in electric/hybrid-electric vehicles provides higher safety in addition to an energy storing capability. Development of a control law for this type of braking system is a challenging task. The antilock braking system (ABS) uses a control strategy to maintain the wheel slip within a predefined range. A sliding mode controller (SMC) for ABS is developed to maintain the optimal slip value. The braking of the vehicle, performed by using both regenerative and antilock braking, is based on an algorithm that decides how to distribute the braking force between the regenerative braking and the antilock braking in emergency/panic braking situations as well as in normal city driving conditions. Detailed bond graph models of a quarter car and four-wheeled vehicles are used in this article to implement and test the control laws. It is found that with combined regenerative and antilock braking, the vehicle’s safety increases (in terms of stopping distance and manoeuvrability) and some amount of kinetic energy can be recovered and stored in the regenerative battery pack. The passenger comfort is improved when a sliding mode ABS controller is used in place of a standard ABS controller for the mechanical braking part. Moreover, the influence of load transfer on the wheels during braking was evaluated on a four-wheeled vehicle model.

scholarly journals Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Lina Wang ◽  
Haihui Zhang
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Control Technique ◽  
Stability And Convergence ◽  
Closed Loop System ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Adaptive Weight ◽  
Fuzzy Sliding Mode ◽  
The Stability

Fuzzy sliding mode control as a robust and intelligent nonlinear control technique is proposed to control processes with severe nonlinearity and unknown models. This paper proposes a new adaptive tracking fuzzy sliding mode controller for nonlinear systems in the presence of fuzzy compensation. The main contribution of the proposed method is that the fuzzy system is used to realize the adaptive approximation of the unknown part of the model, and the fuzzy gain can be reduced effectively. The fuzzy self-adaptive rate is derived through the Lyapunov method, and the stability and convergence of the whole closed-loop system are guaranteed by adjusting the adaptive weight value. The performance of the proposed approach is evaluated for double joint rigid manipulator problems. The simulation results illustrate the effectiveness of our proposed controller.

The Research of Magnetic Levitation System Based on Fuzzy Sliding-Mode Control

2013 ◽  
Vol 380-384 ◽  
pp. 550-555
Author(s):  
Rong Rong Song ◽  
Zi Li Chen
Keyword(s):  
Fuzzy Controller ◽  
Magnetic Levitation ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Control Input ◽  
Closed Loop System ◽  
Fuzzy Sliding Mode Control ◽  
Levitation System ◽  
Fuzzy Sliding Mode ◽  
Magnetic Levitation System

This paper develops a sliding-mode controller with fuzzy rules for the single magnetic levitation system with delay, different signals and interference. The control algorithm comprises a sliding-mode controller which is designed for enhancing robustness when plant uncertainties, and a fuzzy controller which is designed for smoothing the control input when switching at these boundary manifolds. An algorithm is presented for selecting the coefficients of the swithing plane such that the overall closed-loop system has stable eigenvalues. A control input is shown to be smoothing and overcome the chatter. The performance of the single magnetic levitation system is obtained by simulation and experimental results which show that the proposed fuzzy sliding-mode controller algorithm is effective for tracking different signals with interference.

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