Development of an Adaptive Prediction Time Horizon Based Model Predictive Steering Control Algorithm for Autonomous Vehicle With Disturbance Estimation

2020 ◽  
Author(s):  
Kwang-Seok Oh ◽  
Tae-Jun Song
Keyword(s):  
Time Horizon ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Autonomous Vehicle ◽  
System Model ◽  
Prediction Algorithm ◽  
Steering Control ◽  
Disturbance Estimation ◽  
Adaptive Prediction ◽  
Prediction Time

Abstract This paper proposes an adaptive prediction time horizon based model predictive steering control algorithm for autonomous vehicle with disturbance estimation. The model predictive control (MPC) requires relatively accurate system model to compute the reasonable control inputs. There exists model uncertainty between system model and actual system. And the uncertainty can be increased in the prediction step of MPC and that can have an influence on control performance. In order to address the issue, the uncertainty has been estimated using the sliding mode observer and predicted in the designed prediction algorithm based on gray prediction model. Using the predicted future uncertainties, the number of prediction steps has been determined with the uncertainty threshold value. The path tracking control algorithm for autonomous driving has been used to compute the steering angle of vehicle. The performance evaluation of the adaptive MPC has been conducted using the simplified bicycle model in Matlab/Simulink environment under the lane change scenario.

Disturbance Observer Based Tracking Control

1997 ◽  
Vol 122 (2) ◽  
pp. 332-335 ◽  
Author(s):  
Chia-Shang Liu ◽  
Huei Peng
Keyword(s):  
Tracking Control ◽  
Disturbance Observer ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Correction Term ◽  
Superior Performance ◽  
Robot Arm ◽  
Disturbance Estimation ◽  
Control Scheme ◽  
Disturbance Term

A disturbance observer based tracking control algorithm is presented in this paper. The key idea of the proposed method is that the plant nonlinearities and parameter variations can be lumped into a disturbance term. The lumped disturbance signal is estimated based on a plant dynamic observer. A state observer then corrects the disturbance estimation in a two-step design. First, a Lyapunov-based feedback estimation law is used. The estimation is then improved by using a feedforward correction term. The control of a telescopic robot arm is used as an example system for the proposed algorithm. Simulation results comparing the proposed algorithm against a standard adaptive control scheme and a sliding mode control algorithm show that the proposed scheme achieves superior performance, especially when large external disturbances are present. [S0022-0434(00)00802-9]

Collision-avoidance steering control for autonomous vehicles using neural network-based adaptive integral terminal sliding mode

2020 ◽  
Vol 39 (3) ◽  
pp. 4689-4702
Author(s):  
Zhe Sun ◽  
Jiayang Zou ◽  
Defeng He ◽  
Zhihong Man ◽  
Jinchuan Zheng
Keyword(s):  
Neural Network ◽  
Control System ◽  
Collision Avoidance ◽  
Sliding Mode ◽  
Autonomous Vehicle ◽  
Kinematic Model ◽  
Avoidance Performance ◽  
Steering Control ◽  
Terminal Sliding Mode ◽  
Control Scheme

Due to the complex driving conditions confronted by an autonomous vehicle, it is significant for the vehicle to possess a robust control system to achieve effective collision-avoidance performance. This paper proposes a neural network-based adaptive integral terminal sliding mode (NNAITSM) control scheme for the collision-avoidance steering control of an autonomous vehicle. In order to describe the vehicle’s lateral dynamics and path tracking characteristics, a two-degrees-of-freedom (2DOF) dynamic model and a kinematic model are adopted. Then, an NNAITSM controller is designed, where a radial basis function neural network (RBFNN) scheme is utilized to online approximate the optimal upper bound of lumped system uncertainties such that prior knowledge about the uncertainties is not required. The stability of the control system is proved via Lyapunov, and the selection guideline of control parameters is provided. Last, Matlab-Carsim co-simulations are executed to test the performance of the designed controller under different road conditions and vehicle velocities. Simulation results show that compared with conventional sliding mode (CSM) and nonsingular terminal sliding mode (NTSM) control, the proposed NNAITSM control scheme owns evident superiority in not only higher tracking precision but also stronger robustness against various road surfaces and vehicle velocities.

Haptic control of steer-by-wire systems for tracking of target steering feedback torque

2019 ◽  
Vol 234 (5) ◽  
pp. 1389-1401
Author(s):  
Jaepoong Lee ◽  
Kyongsu Yi ◽  
Dongpil Lee ◽  
Bongchoon Jang ◽  
Minjun Kim ◽  
...  
Keyword(s):  
Control Algorithm ◽  
Haptic Feedback ◽  
Sliding Mode ◽  
System Model ◽  
Adaptive Sliding Mode Control ◽  
Steering Wheel ◽  
Infinite Impulse Response ◽  
Steer By Wire ◽  
Steering Torque ◽  
Haptic Control

This study proposes a haptic control of steer-by-wire systems for tracking a target steering feedback torque to achieve the conventional steering feedback torque. The haptic feedback control with a steer-by-wire steering-wheel system model was used to provide drivers with a conventional steering feedback torque. The steer-by-wire steering-wheel system model was developed, and a haptic control algorithm was designed for a desired steering feedback torque with a three-dimensional target steering torque map. In order to track the target steering torque to let the drivers feel the conventional steering efforts, an adaptive sliding-mode control was used to ensure robustness against parameter uncertainty. The angular velocity and angular acceleration used in the control algorithm were estimated using an infinite impulse response filter. The performance of the proposed controller was evaluated by computer simulation and hardware-in-the-loop simulation tests under various steering conditions. The proposed haptic controller successfully tracked the steering feedback torque for steer-by-wire systems.

Research on Steering Control and Simulation of Vehicle Steer-by-Wire System

2011 ◽  
Vol 403-408 ◽  
pp. 5076-5081 ◽  
Author(s):  
Xu Yun Qiu ◽  
Ming Jin Yu ◽  
Zhu Lin Zhang ◽  
Jiu Hong Ruan
Keyword(s):  
Disturbance Rejection ◽  
Control Algorithm ◽  
System Model ◽  
Tire Model ◽  
Steering Control ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Steer By Wire ◽  
Wire System ◽  
Motor Model

A simulation model of Steer-by-Wire(SBW) is built, including steering motor model, steering executive system model, vehicle model and Fiala tire model. Based on the Linear Active Disturbance Rejection Control(LADRC) technique, a kind of control algorithm on steer angle of vehicle SBW is designed. On the simulation system, the control algorithm is simulated and test. The results show that the LADRC controller can implement high precision and strong robust control effects on steer control of vehicle SBW system.

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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