Design of slip-based traction control system for EV and validation using co-simulation between Adams and Matlab/Simulink

SIMULATION ◽  
2020 ◽  
Vol 96 (6) ◽  
pp. 537-549 ◽  
Author(s):  
Sudipta Saha ◽  
Syed Muhammad Amrr
Keyword(s):  
Control Method ◽  
Sliding Mode ◽  
Open Loop ◽  
Control Technique ◽  
Parameter Uncertainties ◽  
Slip Ratio ◽  
Matlab Simulink ◽  
3D Cad ◽  
Longitudinal Slip ◽  
Parameter Values

This paper focuses on controlling traction for a four-wheel electric vehicle by using the longitudinal slip ratio control technique. By keeping the slip ratio value inside an optimal limit, it can be ensured that the maximum driving force is obtainable by increasing the friction force between tire and road. The usefulness of the sliding mode control method is to provide robust performance from the parameter uncertainties at different road conditions. A control law is formulated based upon the Lyapunov stability approach to assure the sliding action. To satisfy the robustness, a vehicle model is made in Matlab, and it is simulated based on various parameter values. The slip ratios at different parameter values are plotted for open loop and closed loop. Then considering the vehicle kinematics and dynamics, a 3D CAD model using Catia is developed. Then exporting the model to Adams to use it as a plant model for the vehicle, co-simulation has been achieved by keeping the slip-based traction controller in Matlab/Simulink. Matlab/Simulink and Adams/View simulation validate the proposed method.

scholarly journals Flatness-Based Control of a Two Degrees-of-Freedom Platform With Pneumatic Artificial Muscles

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
David Bou Saba ◽  
Paolo Massioni ◽  
Eric Bideaux ◽  
Xavier Brun
Keyword(s):  
Degrees Of Freedom ◽  
Control Method ◽  
Sliding Mode ◽  
Feedforward Control ◽  
Volume Ratio ◽  
Open Loop ◽  
Control Technique ◽  
Artificial Muscles ◽  
Two Degrees Of Freedom ◽  
Pneumatic Artificial Muscles

Pneumatic artificial muscles (PAMs) are an interesting type of actuators as they provide high power-to-weight and power-to-volume ratio. However, their efficient use requires very accurate control methods taking into account their complex and nonlinear dynamics. This paper considers a two degrees-of-freedom platform whose attitude is determined by three pneumatic muscles controlled by servovalves. An overactuation is present as three muscles are controlled for only two degrees-of-freedom. The contribution of this work is twofold. First, whereas most of the literature approaches the control of systems of similar nature with sliding mode control, we show that the platform can be controlled with the flatness-based approach. This method is a nonlinear open-loop controller. In addition, this approach is model-based, and it can be applied thanks to the accurate models of the muscles, the platform and the servovalves, experimentally developed. In addition to the flatness-based controller, which is mainly a feedforward control, a proportional-integral (PI) controller is added in order to overcome the modeling errors and to improve the control robustness. Second, we solve the overactuation of the platform by an adequate choice for the range of the efforts applied by the muscles. In this paper, we recall the basics of this control technique and then show how it is applied to the proposed experimental platform. At the end of the paper, the proposed approach is compared to the most commonly used control method, and its effectiveness is shown by means of experimental results.

scholarly journals A Modified RBF Neuro-Sliding Mode Control Technique for a Grid Connected PMSG Based Variable Speed Wind Energy Conversion System

2018 ◽  
Vol 2018 ◽  
pp. 1-19
Author(s):  
Rostand Marc Douanla ◽  
Godpromesse Kenné ◽  
François Béceau Pelap ◽  
Armel Simo Fotso
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Control Technique ◽  
Nonlinear Controller ◽  
Parameter Uncertainties ◽  
Power Extraction ◽  
Mode Control ◽  
The Neural Network

A modified control scheme based on the combination of online trained neural network and sliding mode techniques is proposed to enhance maximum power extraction for a grid connected permanent magnet synchronous generator (PMSG) wind turbine system. The proposed control method does not need the knowledge of the uncertainty bounds nor the exact model of the nonlinear system. Since the neural network is trained online, the time to estimate good weights can affect the dynamic performance of the process during the startup phase. Therefore an appropriate way to smoothly and explicitly accelerate the neural network rate of convergence during the startup phase is proposed. Furthermore, a flexible grid side voltage source converter control structure which can handle both grid connected and standalone modes based on conventional proportional integral (PI) control method is presented. Simulations are done in Matlab/Simulink environment to verify the effectiveness and assess the performance of the proposed controller. The results analysis shows the superiority of the proposed RBF neuro-sliding mode controller compared to a nonlinear controller based on sliding mode control method when the system undergoes parameter uncertainties.

scholarly journals A sliding mode algorithm for antilock braking/traction control of EVs

2015 ◽  
Vol 18 (3) ◽  
pp. 174-182 ◽  
Author(s):  
Minh Ngoc Vu ◽  
Minh Cao Ta
Keyword(s):  
Electric Vehicles ◽  
Driving Force ◽  
Control Method ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Control Performance ◽  
Slip Ratio ◽  
Traction Control ◽  
Road Condition ◽  
Wheel Model

This paper presents a slip suppression controller using sliding mode control method for electric vehicles which aims to improve the control performance of Evs in both driving and braking mode. In this method, a sliding mode controller is designed to obtain the maximum driving force by suppressing the slip ratio. The numerical simulations for one wheel model under variations in mass of vehicle and road condition are performed and demonstrated to show the effectiveness of the proposed method.

Adaptive altitude flight control of quadcopter under ground effect and time-varying load: theory and experiments

2021 ◽  
pp. 107754632110501
Author(s):  
Ji-Won Lee ◽  
Nguyen Xuan-Mung ◽  
Ngoc Phi Nguyen ◽  
Sung Kyung Hong
Keyword(s):  
Flight Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Ground Effect ◽  
Lyapunov Theory ◽  
Control Technique ◽  
Time Varying ◽  
Control Performance ◽  
Parameter Uncertainties ◽  
Altitude Control

In recent years, the boom of the quadcopter industry resulted in a broad range of real-world applications which highlighted the urgent need to improve quadcopter control quality. Typically, external disturbances, such as wind, parameter uncertainties caused by payload variations, or the ground effect, can severely degrade the quadcopter’s altitude control performance. Meanwhile, widely used controllers like the proportional-integral-derivative control cannot guarantee control performance when the system is critically affected by factors that exhibit a high degree of variability with time. In this paper, an adaptive control algorithm is proposed to improve quadcopter altitude tracking performance in the presence of both the ground effect and a time-varying payload. First, we derive an adaptive altitude control algorithm using the sliding mode control technique to account for these uncertainties in the quadcopter dynamics model. Second, we apply Lyapunov theory to analyze the stability of the closed-loop system. Finally, we conduct several numerical simulations and experiments to validate the effectiveness of the proposed method.

A sky-hook sliding mode semiactive control for commercial truck seat suspension

2020 ◽  
pp. 107754632094097
Author(s):  
Qiang Chen ◽  
Yong Zhang ◽  
Chengwei Zhu ◽  
Jinbo Wu ◽  
Ye Zhuang
Keyword(s):  
Nonlinear System ◽  
Phase Portrait ◽  
Control Method ◽  
Reference Model ◽  
Sliding Mode ◽  
Tracking Error ◽  
Magnetorheological Damper ◽  
Nonlinear Controller ◽  
Parameter Uncertainties ◽  
Seat Suspension

A semiactive seat suspension control method is proposed in this study and applied to attenuate the vibration of the commercial truck seat for enhancing its ride comfort. The semiactive seat suspension system with a magnetorheological damper behaves with undesirable nonlinear properties. The proposed controller is a typical nonlinear controller, which takes the ideal sky-hook controller as the reference model and forces the tracking error vector. The controller has achieved great performance of attenuating vibration and is robust to parameter uncertainties and external disturbances. The relaxation oscillation phenomenon and convergence were also analyzed by the contribution of the phase portrait. As the phase portrait depicted, the sky-hook controller, a weakly nonlinear system, could be approximated by the equivalent linear approximate model. However, the proposed controller, the sky-hook sliding mode controller, is a strongly nonlinear system, which could not be linearized by the regular perturbation theory, and the criterion is given by the phase portrait. The experiment results showed good agreement with the simulation results, and some other matters encountered were also analyzed in the process of application.

Nonlinear and Machine-Learning-Based Station-Keeping Control of an Unmanned Surface Vehicle

2020 ◽  
Author(s):  
Armando J. Sinisterra ◽  
Alexandrea Barker ◽  
Siddhartha Verma ◽  
Manhar R. Dhanak
Keyword(s):  
Machine Learning ◽  
Tracking Control ◽  
Situational Awareness ◽  
Control Method ◽  
Sliding Mode ◽  
Control Technique ◽  
Station Keeping ◽  
Trajectory Tracking Control ◽  
Ongoing Work ◽  
Machine Learning Approach

Abstract This study is part of ongoing work on situational awareness and autonomy of a 16’ WAM-V USV. The objective of this work is to determine the potential and merits of application of two different station-keeping controllers for a fixed-pose motion control of the USV. The assessment includes performance and power consumption metrics tested under harsh environmental disturbances to evaluate the robustness of the control methods. The first is a nonlinear trajectory-tracking control method based on the sliding-mode control technique, while the second method uses a machine-learning approach based on Deep Reinforcement Learning. Results from both the approaches are compared for various case studies.

scholarly journals Adaptive output feedback integral sliding mode attitude tracking control of spacecraft without unwinding

2017 ◽  
Vol 9 (7) ◽  
pp. 168781401771040 ◽  
Author(s):  
Anuchit Jitpattanakul ◽  
Chutiphon Pukdeboon
Keyword(s):  
Output Feedback ◽  
Tracking Control ◽  
Sliding Mode ◽  
Control Technique ◽  
Control Law ◽  
Parameter Uncertainties ◽  
External Disturbances ◽  
Integral Sliding Mode ◽  
Attitude Tracking ◽  
Attitude Tracking Control

This article studies an output feedback attitude tracking control problem for rigid spacecraft in the presence of parameter uncertainties and external disturbances. First, an anti-unwinding attitude control law is designed using the integral sliding mode control technique to achieve accurate tracking responses and robustness against inertia uncertainties and external disturbances. Next, the derived control law is combined with a suitable tuning law to relax the knowledge about the bounds of uncertainties and disturbances. The stability results are rigorously proved using the Lyapunov stability theory. In addition, a new finite-time sliding mode observer is developed to estimate the first time derivative of attitude. A new adaptive output feedback attitude controller is designed based on the estimated results, and angular velocity measurements are not required in the design process. A Lyapunov-based analysis is provided to demonstrate the uniformly ultimately bounded stability of the observer errors. Numerical simulations are given to illustrate the effectiveness of the proposed control method.

Tracking Control Design for Quadrotor Unmanned Aerial Vehicle

2017 ◽  
Vol 67 (3) ◽  
pp. 245 ◽  
Author(s):  
Sudhir Nadda ◽  
A. Swarup
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Control Strategy ◽  
Tracking Control ◽  
Control Method ◽  
Sliding Mode ◽  
Backstepping Control ◽  
Control Technique ◽  
Quadrotor Uav ◽  
Attitude Tracking ◽  
Aerial Vehicle

The model of a quadrotor unmanned aerial vehicle (UAV) is nonlinear and dynamically unstable. A flight controller design is proposed on the basis of Lyapunov stability theory which guarantees that all the states remain and reach on the sliding surfaces. The control strategy uses sliding mode with a backstepping control to perform the position and attitude tracking control. This proposed controller is simple and effectively enhance the performance of quadrotor UAV. In order to demonstrate the robustness of the proposed control method, White Gaussian Noise and aerodynamic moment disturbances are taken into account. The performance of the nonlinear control method is evaluated by comparing the performance with developed linear quadratic regulator and existing backstepping control technique and proportional-integral-derivative from the literature. The comparative performance results demonstrate the superiority and effectiveness of the proposed control strategy for the quadrotor UAV.

scholarly journals Smooth Sliding Mode Control for Vehicle Rollover Prevention Using Active Antiroll Suspension

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Duanfeng Chu ◽  
Xiao-Yun Lu ◽  
Chaozhong Wu ◽  
Zhaozheng Hu ◽  
Ming Zhong
Keyword(s):  
Sliding Mode Control ◽  
Load Transfer ◽  
Control Method ◽  
Sliding Mode ◽  
Dynamics Simulation ◽  
Control Technique ◽  
Simulating Experiment ◽  
Mode Control ◽  
Rollover Prevention ◽  
Robust Stability Analysis

The rollover accidents induced by severe maneuvers are very dangerous and mostly happen to vehicles with elevated center of gravity, such as heavy-duty trucks and pickup trucks. Unfortunately, it is hard for drivers of those vehicles to predict and prevent the trend of the maneuver-induced (untripped) rollover ahead of time. In this study, a lateral load transfer ratio which reflects the load distribution of left and right tires is used to indicate the rollover criticality. An antiroll controller is designed with smooth sliding mode control technique for vehicles, in which an active antiroll suspension is installed. A simplified second order roll dynamic model with additive sector bounded uncertainties is used for control design, followed by robust stability analysis. Combined with the vehicle dynamics simulation package TruckSim, MATLAB/Simulink is used for simulating experiment. The results show that the applied controller can improve the roll stability under some typical steering maneuvers, such as Fishhook and J-turn. This direct antiroll control method could be more effective for untripped rollover prevention when driver deceleration or steering is too late. It could also be extended to handle tripped rollovers.

scholarly journals Control of Chaos in Rate-Dependent Friction-Induced Vibration Using Adaptive Sliding Mode Control and Impulse Damper

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Ehsan Maani Miandoab ◽  
Aghil Yousefi-Koma ◽  
Saeed Hashemnia
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Control Technique ◽  
Adaptive Sliding Mode Control ◽  
Control Law ◽  
Adaptive Sliding Mode ◽  
Chaotic Vibration ◽  
Mode Control ◽  
Rate Dependent

Two different control methods, namely, adaptive sliding mode control and impulse damper, are used to control the chaotic vibration of a block on a belt system due to the rate-dependent friction. In the first method, using the sliding mode control technique and based on the Lyapunov stability theory, a sliding surface is determined, and an adaptive control law is established which stabilizes the chaotic response of the system. In the second control method, the vibration of this system is controlled by an impulse damper. In this method, an impulsive force is applied to the system by expanding and contracting the PZT stack according to efficient control law. Numerical simulations demonstrate the effectiveness of both methods in controlling the chaotic vibration of the system. It is shown that the settling time of the controlled system using impulse damper is less than that one controlled by adaptive sliding mode control; however, it needs more control effort.

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