A comprehensive active-steering control method for improvement of vehicle handling performance

2017 ◽  
Vol 232 (3) ◽  
pp. 413-425 ◽  
Author(s):  
Weimiao Yang ◽  
Pengpeng Feng ◽  
Jianwu Zhang
Keyword(s):  
Linear System ◽  
Feedback Linearization ◽  
Control Method ◽  
System Control ◽  
Steering Control ◽  
Vehicle Handling ◽  
Handling Performance ◽  
Non Linear ◽  
Tyre Modelling ◽  
Non Linear System

Non-linear system control has always been a difficult point for vehicle stabilization. To improve the vehicle handling performance, a comprehensive active-steering control method is proposed and derived. Different from traditional strategy, this new controller is based on a piecewise tyre modelling ideology combined with feedback linearization controlling method. In the linear region of wheel–terrain contact, vehicle dynamic system turns to be a linear system, an optimal control is designed for the sake of rapid response in tracking desired values. In the non-linear region, where the controlling difficulty always lies in, the tyre lateral force is described by a new polynomial formula model, which is simpler than magic formula model and more accurate than linear model. This new tyre modelling ideology ensures the feasibility of feedback linearization method in non-linear system control. To verify the proposed controller, a numerical seven-degrees-of-freedom vehicle model is built and validated by standard input simulation. Then, simulation under limit conditions, including high friction case and low friction case, are conducted and results are presented and discussed. Compared with optimal controller and free-control method, comprehensive controller has a much more desirable applicability in both cases and greatly improves the vehicle handling performance.

A novel robust fuzzy control of an uncertain system

2016 ◽  
Vol 39 (3) ◽  
pp. 324-333 ◽  
Author(s):  
Abdurrahman Bayrak ◽  
Handan Gürsoy ◽  
Mehmet Önder Efe
Keyword(s):  
Linear System ◽  
Fuzzy Control ◽  
Control Method ◽  
Sliding Mode ◽  
Poor Performance ◽  
Uncertain System ◽  
Step Response ◽  
Non Linear ◽  
Non Linear System ◽  
Noisy Measurements

This paper presents a robust control method combining the conventional proportional–integral–derivative (PID) scheme and the sliding mode fuzzy control scheme for a second-order non-linear system having uncertainties in the system dynamics. The goal of the proposed scheme is to force the response of the uncertain plant to follow that of the nominal model. The first phase of the design approach is to obtain a nominal PID controller for the nominal plant model. The poor performance of the sole PID scheme on the uncertain non-linear system motivates the proposal of the technique discussed here. To compensate for the deficiencies in the unit step response of the uncertain system, a fuzzy compensation scheme based on sliding mode control (SMC) is proposed and the PID loop is augmented by the proposed approach. It is shown that the performance with the proposed scheme is better than the sole PID-based control system. With the proposed technique, the response of the uncertain system converges to of the nominal system with admissible controller outputs. Furthermore, simulation results show that the proposed method produces consistent results even with noisy measurements.

A novel LSSVM-L Hammerstein model structure for system identification and nonlinear model predictive control of CSTR servo and regulatory control

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Akshaykumar Naregalkar ◽  
Subbulekshmi Durairaj
Keyword(s):  
Linear System ◽  
Regulatory Control ◽  
Hammerstein Model ◽  
Support Vector ◽  
Model Structure ◽  
Linear Dynamics ◽  
Vector Machines ◽  
Non Linear ◽  
Laguerre Filters ◽  
Non Linear System

Abstract A continuous stirred tank reactor (CSTR) servo and the regulatory control problem are challenging because of their highly non-linear nature, frequent changes in operating points, and frequent disturbances. System identification is one of the important steps in the CSTR model-based control design. In earlier work, a non-linear system model comprises a linear subsystem followed by static nonlinearities and represented with Laguerre filters followed by the LSSVM (least squares support vector machines). This model structure solves linear dynamics first and then associated nonlinearities. Unlike earlier works, the proposed LSSVM-L (least squares support vector machines and Laguerre filters) Hammerstein model structure solves the nonlinearities associated with the non-linear system first and then linear dynamics. Thus, the proposed Hammerstein’s model structure deals with the nonlinearities before affecting the entire system, decreasing the model complexity and providing a simple model structure. This new Hammerstein model is stable, precise, and simple to implement and provides the CSTR model with a good model fit%. Simulation studies illustrate the benefit and effectiveness of the proposed LSSVM-L Hammerstein model and its efficacy as a non-linear model predictive controller for the servo and regulatory control problem.

On a non-linear system for shape memory alloys

1990 ◽  
Vol 2 (1) ◽  
pp. 65-76 ◽  
Author(s):  
Ph. B�nilan ◽  
D. Blanchard ◽  
H. Ghidouche
Keyword(s):  
Linear System ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Non Linear ◽  
Non Linear System
Sign in / Sign up

Export Citation Format

Share Document