Sliding Mode Control of the Vehicle Speed System Based on LMIs

Hong-Liang Gao,Hong-Cong Zhang,Xiao-Ling Li,Heng Liu

doi:10.1155/2021/5535213

Abstract

Due to the nonlinear characteristics of the vehicle speed system, its stability is difficult to control. This paper analyzes the stability and traceability of the vehicle speed system under nonlinear characteristics. A sliding mode control method of the nonlinear system state observation based on linear matrix inequalities (LMIs) is proposed. In the proposed control method, Lyapunov function is used as the control function to track the position and speed of the vehicle speed system in real time. In the design process of the controller, the successive scaling method (SSM) is designed to improve the tracking accuracy. The simulation results demonstrate that the sliding mode control can effectively track the position of the vehicle speed system, which has better stability and traceability for the nonlinear vehicle speed system.

Highlights

Complexity and efficient solution for naturally fractured reservoir simulation
In [21], the input-output dynamic stability of networked physical systems was studied. e given networked physical systems are transformed into logical networks with the same robustness. e robustness of networked physical systems is analyzed, and the design method is applied to the robustness analysis of infinite bus systems
A robust chattering-free control scheme was proposed, and the parameters of the controller were given in the form of linear matrix inequalities (LMIs). e control structure is independent of the order of the model, and the simulation results in Genesio’s chaotic system and Chua’s circuit system verify the effectiveness of the scheme

Summary

Preliminaries

Y kx, where x 􏼂 x1 x2 􏼃T, x is the state vector, u is the control input, let u gφ, and g is a coefficient related to vehicle weight, φ represents traction or braking force, h represents the disturbance of the vehicle speed system, y is the system output, and k represents the scale factor of the vehicle position. X1 and x2 are the position and speed of the vehicle speed system, respectively At this time, the practical problem can be transformed into the observer-related problem.

Main Results

Design the sliding mode function:

Simulation

Conclusion