Cancellation of Unnatural Reaction Torque in Variable-Gear-Ratio

2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Sumio Sugita ◽  
Masayoshi Tomizuka
Keyword(s):  
Control Method ◽  
Gear Ratio ◽  
Hardware In The Loop ◽  
Simple Concept ◽  
Active Steering ◽  
Reaction Torque

Variable-gear-ratio steering, also known as active steering, is an advanced steering technology which enhances the driver’s comfort and vehicle operability. However, one big problem, namely the unnatural reaction torque created by the variable actuator, restricts the further practical-use of the variable-gear-ratio steering. This paper proposes a control method to cancel the unnatural torque using a simple concept called friction relocation. Effectiveness of the method is experimentally confirmed using a hardware-in-the-loop simulator.

Control Design for Cancellation of Unnatural Reaction Torque and Vibrations in Variable-Gear-Ratio Steering System

2013 ◽  
Author(s):  
Atsushi Oshima ◽  
Xu Chen ◽  
Sumio Sugita ◽  
Masayoshi Tomizuka
Keyword(s):  
Control Method ◽  
Low Frequency ◽  
Control Design ◽  
Steering System ◽  
Gear Ratio ◽  
Experimental Setup ◽  
Hardware In The Loop ◽  
Model Uncertainties ◽  
Reaction Torque

Variable-gear-ratio steering is an advanced feature in automotive vehicles. As the name suggest, it changes the steering gear ratio depending on the speed of the vehicle. This feature can simplify steering for the driver, which leads to various advantages, such as improved vehicle comfort, stability, and safety. One serious problem, however, is that the variable-gear-ratio system generates unnatural torque to the driver whenever the variable-gear-ratio control is activated. Such unnatural torque includes both low-frequency and steering-speed-dependent components. This paper proposes a control method to cancel this unnatural torque. We address the problem by using a tire sensor and a set of feedback and feedforward algorithms. Effectiveness of the proposed method is experimentally verified using a hardware-in-the-loop experimental setup. Stability and robustness under model uncertainties are evaluated.

scholarly journals Research on Model Predictive Control Method for Vehicle Lateral Stability Based on Hardware-in-the-Loop Test

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Jian Wang ◽  
Shifu Liu ◽  
Jian Wu ◽  
Jun Yang ◽  
Aijuan Li
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Model Uncertainty ◽  
Control Method ◽  
Autonomous Driving ◽  
Steering System ◽  
Control Model ◽  
Hardware In The Loop ◽  
Active Steering ◽  
Active Steering System

With the rapid development of the vehicle chassis control and autonomous driving technology, it is more and more urgent to realize the active steering technology of autonomous driving stability control. Under emergency conditions, the adhesion constraints, the model uncertainty, and the strong nonlinearity of vehicle bring great challenges to active steering control. In this paper, a model predictive control method for an active steering system based on a nonlinear vehicle model is proposed to solve the problems of adhesion constraint, model uncertainty, and external disturbance in the active steering system. Based on the real-time measurement of vehicle state, a new optimization method is proposed in this paper, which has good performance in dealing with the uncertainty and nonlinearity of the model. The control method transforms the constraint problem into quadratic programming and nonlinear programming. In order to ensure the control accuracy when the vehicle enters the nonlinear area, the control model is built with the combination of the nonlinear tire model and the 2DOF model. The control model is built based on Simulink, and the effectiveness of the controller is the verified joint simulation of Simulink and CarSim. The hardware-in-the-loop (HIL) test bench based on LabVIEW RT is built and tested in order to verify the feasibility and real effect of the controller. Simulation and HIL test results demonstrate that, compared with PID controller, the model predictive controller can accomplish the driving task well and improve the vehicle handling stability.

Research on Adaptive PID Control for Load Simulator with Varying Load

2014 ◽  
Vol 568-570 ◽  
pp. 1031-1035
Author(s):  
Ju Tian ◽  
Yao Chen
Keyword(s):  
Pid Control ◽  
Simple Structure ◽  
Control Method ◽  
Parameter Tuning ◽  
Hardware In The Loop ◽  
Tuning Method ◽  
Hydraulic Load ◽  
Variation Characteristics ◽  
Load Simulator ◽  
Adaptive Pid Control

The electro-hydraulic load simulator is an important equipment for aircraft hardware-in-the-loop simulation. An adaptive PID control method for compensating extraneous torque with simple structure and easy to implement is proposed according to the variation characteristics of load gradient in the load simulator. The control parameter tuning method is also given.

scholarly journals Research on vehicle active steering control based on linear matrix inequality and hardware in the loop test scheme design and implement for active steering

2019 ◽  
Vol 11 (11) ◽  
pp. 168781401989210 ◽  
Author(s):  
Guangfei Xu ◽  
Peisong Diao ◽  
Xiangkun He ◽  
Jian Wu ◽  
Guosong Wang ◽  
...  
Keyword(s):  
Linear Matrix Inequality ◽  
Model Uncertainty ◽  
Control Method ◽  
Steering System ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Steering Control ◽  
Sensor Noise ◽  
Active Steering ◽  
Active Steering Control

In the research process of automotive active steering control, due to the model uncertainty, road surface interference, sensor noise, and other influences, the control accuracy of the active steering system will be reduced, and the driver’s road sense will become worse. The traditional robust controller can solve the model uncertainty, pavement disturbance and sensor noise in the design process, but cannot consider the performance enough. Therefore, this article proposes an active steering control method based on linear matrix inequality. In this method, the model uncertainty, road interference, sensor noise, yaw velocity, and slip side angle tracking errors are all considered as constraint targets, respectively, so that the performance and robust stability of the active front steering system can be guaranteed. Finally, simulation and hardware in the loop experiment are implemented to verify the effect of active front steering system under the linear matrix inequality controller. The results show that the proposed control method can achieve better robust performance and robust stability.

Hardware-in-the-Loop Simulation for Active Force Control with Iterative Learning Applied to an Active Vehicle Suspension System

2013 ◽  
Vol 465-466 ◽  
pp. 801-805
Author(s):  
Rosmazi Rosli ◽  
Musa Mailah ◽  
Gigih Priyandoko
Keyword(s):  
Force Control ◽  
Control Method ◽  
Learning Algorithm ◽  
Suspension System ◽  
Iterative Learning ◽  
Practical Implementation ◽  
Hardware In The Loop ◽  
Active Force ◽  
Physical Test ◽  
Active Force Control

The paper focuses on the practical implementation of a novel control method to an automotive suspension system using active force control (AFC) with iterative learning algorithm (ILA) and proportional-integral-derivative (PID) control strategy. The overall control system to be known as AFC-IL scheme essentially comprises three feedback control loops to cater for a number of specific tasks, namely, the innermost loop for the force tracking of the pneumatic actuator using PI controller, intermediate loops applying AFC with ILA strategy for the compensation of the disturbances and the outermost loop using PID controller for the computation of the desired force. A number of experiments were carried out on a physical test rig with hardware-in-the-loop simulation (HILS) feature that fully incorporates the theoretical elements. The performance of the proposed control method was evaluated and benchmarked to examine the effectiveness of the system in suppressing the vibration effect of the suspension system. It was found that the experimental results demonstrate the superiority of the active suspension system with proposed AFC-IL scheme compared to the PID and passive counterparts.

scholarly journals Trajectory Tracking Control in Real-Time of Dual-Motor-Driven Driverless Racing Car Based on Optimal Control Theory and Fuzzy Logic Method

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Gang Li ◽  
Sucai Zhang ◽  
Lei Liu ◽  
Xubin Zhang ◽  
Yuming Yin
Keyword(s):  
Optimal Control ◽  
Fuzzy Logic ◽  
Optimal Control Theory ◽  
Tracking Control ◽  
Control Method ◽  
Steering Control ◽  
Trajectory Tracking Control ◽  
Differential Drive ◽  
Active Steering ◽  
Fuzzy Logic Method

To improve the accuracy and timeliness of the trajectory tracking control of the driverless racing car during the race, this paper proposes a track tracking control method that integrates the rear wheel differential drive and the front wheel active steering based on optimal control theory and fuzzy logic method. The model of the lateral track tracking error of the racing car is established. The model is linearized and discretized, and the quadratic optimal steering control problem is constructed. Taking advantage of the differential drive of dual-motor-driven racing car, the dual motors differential drive fuzzy controller is designed and integrated driving with active steering control. Simulation analysis and actual car verification show that this integrated control method can ensure that the car tracks different race tracks well and improve the track tracking control accuracy by nearly 30%.

An adaptive control approach for semi-active suspension systems under unknown road disturbance input using hardware-in-the-loop simulation

2020 ◽  
pp. 014233121989593 ◽  
Author(s):  
Gokhan Kararsiz ◽  
Mahmut Paksoy ◽  
Muzaffer Metin ◽  
Halil Ibrahim Basturk
Keyword(s):  
Adaptive Control ◽  
Control Method ◽  
Active Suspension ◽  
Magnetorheological Damper ◽  
Hardware In The Loop ◽  
Control Approach ◽  
The Road ◽  
Suspension Systems ◽  
Active Suspension Systems ◽  
Road Disturbance

This article presents an application of the adaptive control method to semi-active suspension systems in the presence of unknown disturbance and parametric uncertainty. Due to the technical difficulties such as time delay and sensor noise, the road disturbance is assumed to be unmeasured. To overcome this problem, an observer is designed to estimate the disturbance. It is considered that the road profile consists of a finite number of the sum of sinusoidal signals with unknown amplitudes, phases and frequencies. After the parametrization of the observer, the adaptive control approach is employed to attenuate the effect of the road-induced vibrations using a magnetorheological damper. It is proved that the closed-loop system is stable, despite the adverse road conditions. Finally, the performance of the controller is illustrated with a hardware-in-the-loop simulation in which the system is subjected to sinusoidal and random profile road excitations. To demonstrate the benefits of the adaptive controller, the results are presented in comparison with a conventional proportional integral derivative (PID) controller.

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