scholarly journals STEERING CONTROL FOR ROLLOVER AVOIDANCE OF HEAVY VEHICLE USING FUZZY TUNED PI CONTROLLER

2018 ◽  
Vol 6 (2) ◽  
pp. 128-141
Author(s):  
ANJANA BYJU ◽  
Keyword(s):  
Pi Controller ◽  
Heavy Vehicle ◽  
Steering Control

A hierarchical adaptive control framework of path tracking and roll stability for intelligent heavy vehicle with MPC

2020 ◽  
Vol 234 (13) ◽  
pp. 2933-2946
Author(s):  
Yantao Tian ◽  
Kai Huang ◽  
Xuanhao Cao ◽  
Yulong Liu ◽  
Xuewu Ji
Keyword(s):  
Adaptive Control ◽  
Cooperative Control ◽  
Path Tracking ◽  
Control Mode ◽  
Steering Wheel ◽  
Change Scenario ◽  
Heavy Vehicle ◽  
Steering Control ◽  
Control Framework ◽  
Conflicting Objectives

Roll stability is a major concern in the path tracking process of intelligent heavy vehicles in emergency steering maneuvers. Due to the coupling of lateral and roll motions of heavy vehicle, steering actions for path tracking may come into conflict with that for roll stability. In this paper, a hierarchical adaptive control framework composed of a supervisor, an upper controller and a lower controller is developed to mediate conflicting objectives of path tracking and roll stability via steering control. In the supervisor, path tracking control mode or cooperative control mode of path tracking and roll stability is determined by the predicted rollover index, and a weight function is introduced to balance the control objectives of path tracking and roll stability in cooperative control mode. Then, in order to achieve multi-objective real-time optimization, model predictive control with varying optimization weights is used in the upper controller to calculate the desired front steer angle. The lower controller which integrates the real electrically assisted hydraulic steering system based on Proportional-Integral-Derivative control is designed to control steering wheel angle. Simulation and hardware-in-loop implementation results in double lane change scenario show that the proposed hierarchical adaptive control framework can enhance roll stability in emergency steering maneuvers while keeping the accuracy of path tracking for intelligent heavy vehicle within an acceptable range.

Rollover prevention for a heavy vehicle using optimised slide mode steering control

2019 ◽  
Vol 26 (3/4) ◽  
pp. 351
Author(s):  
Zhilin Jin ◽  
Chao Wang ◽  
Lei Zhang ◽  
Wanzhong Zhao ◽  
Amir Khajepour
Keyword(s):  
Heavy Vehicle ◽  
Steering Control ◽  
Rollover Prevention

Rollover prevention for a heavy vehicle using optimised slide mode steering control

2019 ◽  
Vol 26 (3/4) ◽  
pp. 351
Author(s):  
Amir Khajepour ◽  
Wanzhong Zhao ◽  
Zhilin Jin ◽  
Lei Zhang ◽  
Chao Wang
Keyword(s):  
Heavy Vehicle ◽  
Steering Control ◽  
Rollover Prevention

Influence of different fuzzy operators on analytical structure and variable gains of typical interval type-2 fuzzy PI controller

2020 ◽  
Vol 39 (3) ◽  
pp. 4319-4329
Author(s):  
Haibo Zhou ◽  
Chaolong Zhang ◽  
Shuaixia Tan ◽  
Yu Dai ◽  
Ji’an Duan ◽  
...  
Keyword(s):  
Pi Controller ◽  
Real Time Control ◽  
Fuzzy Operators ◽  
Fuzzy Operator ◽  
Analytical Structure ◽  
Product Operator ◽  
Pi Controllers ◽  
Fuzzy Pi Controller ◽  
Interval Type

The fuzzy operator is one of the most important elements affecting the control performance of interval type-2 (IT2) fuzzy proportional-integral (PI) controllers. At present, the most popular fuzzy operators are product fuzzy operator and min() operator. However, the influence of these two different types of fuzzy operators on the IT2 fuzzy PI controllers is not clear. In this research, by studying the derived analytical structure of an IT2 fuzzy PI controller using typical configurations, it is proved mathematically that the variable gains, i.e., proportional and integral gains of typical IT2 fuzzy PI controllers using the min() operator are smaller than those using the product operator. Moreover, the study highlights that unlike the controllers based on the product operator, the controllers based on the min() operator have a simple analytical structure but provide more control laws. Real-time control experiments on a linear motor validate the theoretical results.

THE SETTINGS ALGORITHM OF A NEURO-FUZZY PI-CONTROLLER

2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Atamurat Mambetov ◽  
Rasul Beglerbekov ◽  
Hurliman Sultanova
Keyword(s):  
Pi Controller ◽  
Neuro Fuzzy ◽  
Fuzzy Pi Controller

Adjust Method of Nonlinear Gain in Four-Wheel Steering Control Using Sliding Mode Control

2009 ◽  
Vol 129 (7) ◽  
pp. 1389-1396 ◽  
Author(s):  
Misawa Kasahara ◽  
Yuki Kanai ◽  
Ryoko Shiraki ◽  
Yasuchika Mori
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Steering Control ◽  
Nonlinear Gain ◽  
Mode Control
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