scholarly journals Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2812
Author(s):  
Yonghwan Jeong ◽  
Seongjin Yim
Keyword(s):  
Linear Time ◽  
Integrated Control ◽  
Autonomous Vehicle ◽  
Path Tracking ◽  
Reference State ◽  
Time Varying ◽  
Motion Controller ◽  
Control Effort ◽  
Vehicle Motion ◽  
Multiple Actuators

This paper presents an MPC-based integrated control algorithm for an autonomous vehicle equipped with four-wheel independent steering and driving systems. The objective of this research is to improve the performance of the path and velocity tracking controllers by distributing the control effort to the multiple actuators. The proposed algorithm has two modules: reference state decision and MPC-based vehicle motion controller. Reference state decision module determines reference state profiles consisting of yaw rate and velocity in order to overcome the limitation of the error dynamics-based path tracking controller, which requires several assumptions on the reference path. The MPC-based vehicle motion controller is designed with a linear time-varying vehicle model in order to optimally allocate the control effort to each actuator. A linear time-varying MPC is adopted to reduce computational burden caused by using a non-linear one. The effectiveness of the proposed algorithm is validated via simulation on MATLAB/Simulink and CarSim. The simulation results show that the proposed algorithm improves the reference tracking performance by effectively distributing the control effort to the steering angle and driving force of each actuator.

Linear time varying model based model predictive control for lateral path tracking

2018 ◽  
Vol 75 (1/2/3/4) ◽  
pp. 1
Author(s):  
Charles Pinto ◽  
Ione Nieva ◽  
Sara Mata ◽  
Itziar Cabanes ◽  
Asier Zubizarreta
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Linear Time ◽  
Path Tracking ◽  
Time Varying ◽  
Model Based

Autonomous vehicle path tracking control considering the stability under lane change

2021 ◽  
pp. 095965182199135
Author(s):  
Xiaolong Chen ◽  
Bing Zhou ◽  
Xiaojian Wu
Keyword(s):  
Tracking Control ◽  
High Speed ◽  
Unscented Kalman Filter ◽  
Linear Time ◽  
Autonomous Vehicle ◽  
Path Tracking ◽  
Steering Angle ◽  
Adhesion Coefficient ◽  
The Road ◽  
Vehicle Path

Considering that when a vehicle travels on a low friction coefficient road with high speed, the path tracking ability declines. To keep the performance of path tracking and improve the stabilization under that situation, this article presents approaches to estimate the parameters and control the vehicle. First, the key states of the vehicle and the road adhesion coefficient are estimated by the unscented Kalman filter. This is followed by applying the linear time-varying model-based predictive controller to achieve path tracking control, and the initial tire steering angle control rate is obtained. Finally, the steering angle compensation controller is simultaneously designed by a simple receding horizon corrector algorithm to improve vehicle stability when the path is tracked on a low-adhesion coefficient or at high speed. The performance of the proposed approach is evaluated by software CarSim and MATLAB/Simulink. Simulation results show that an improvement in the performance of path tracking and stabilization can be achieved by the integrated controller under the variable road adhesion coefficient condition and high speed with 110 km/h.

Linear time varying model based model predictive control for lateral path tracking

2017 ◽  
Vol 75 (1/2/3/4) ◽  
pp. 1 ◽  
Author(s):  
Sara Mata ◽  
Asier Zubizarreta ◽  
Itziar Cabanes ◽  
Ione Nieva ◽  
Charles Pinto
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Linear Time ◽  
Path Tracking ◽  
Time Varying ◽  
Model Based

scholarly journals The VIT Transform Approach to Discrete-Time Signals and Linear Time-Varying Systems

Eng ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 99-125
Author(s):  
Edward W. Kamen
Keyword(s):  
Discrete Time ◽  
Initial Conditions ◽  
Linear Time ◽  
Order Term ◽  
Initial Time ◽  
Time Varying ◽  
Varying Coefficients ◽  
Time Signals ◽  
Time Varying Systems ◽  
Time Varying Coefficients

A transform approach based on a variable initial time (VIT) formulation is developed for discrete-time signals and linear time-varying discrete-time systems or digital filters. The VIT transform is a formal power series in z−1, which converts functions given by linear time-varying difference equations into left polynomial fractions with variable coefficients, and with initial conditions incorporated into the framework. It is shown that the transform satisfies a number of properties that are analogous to those of the ordinary z-transform, and that it is possible to do scaling of z−i by time functions, which results in left-fraction forms for the transform of a large class of functions including sinusoids with general time-varying amplitudes and frequencies. Using the extended right Euclidean algorithm in a skew polynomial ring with time-varying coefficients, it is shown that a sum of left polynomial fractions can be written as a single fraction, which results in linear time-varying recursions for the inverse transform of the combined fraction. The extraction of a first-order term from a given polynomial fraction is carried out in terms of the evaluation of zi at time functions. In the application to linear time-varying systems, it is proved that the VIT transform of the system output is equal to the product of the VIT transform of the input and the VIT transform of the unit-pulse response function. For systems given by a time-varying moving average or an autoregressive model, the transform framework is used to determine the steady-state output response resulting from various signal inputs such as the step and cosine functions.

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