Optimal Sliding Mode Control for an Active Suspension System Based on a Genetic Algorithm

Abstract

In order to improve the dynamic quality of traditional sliding mode control for an active suspension system, an optimal sliding mode control (OSMC) based on a genetic algorithm (GA) is proposed. First, the overall structure and control principle of the active suspension system are introduced. Second, the mathematical model of the quarter car active suspension system is established. Third, a sliding mode control (SMC) controller is designed to manipulate the active force to control the active suspension system. Fourth, GA is applied to optimize the weight coefficients of an SMC switching function and the parameters of the control law. Finally, the simulation model is built based on MATLAB/Simulink (version 2014a), and the simulations are performed and analyzed with the proposed control strategy to identify its performance. The simulation results show that the OSMC controller tuned using a GA has better control performance than the traditional SMC controller.

Evaluation of the stability enhancement of the conventional sliding mode controller using whale optimization algorithm

“…Numerous conventional methods were offered for addressing this issue; one of them is substituting the Sign mathematical function, which is considered the cause of the chattering phenomenon by another model [16,17]. While some solutions were based on the integration between CSMCR and smart fuzzy controller [18], some of the Optimization techniques also investigated to reduce chattering impact such as genetic and particle swarm algorithms [19][20][21][22][23]. However; the deployment of optimization algorithms requires further investigation to illustrate the feasibility of the advanced techniques over classical mathematical models, the proposed work mainly aims to utilize a highly advanced whale optimization algorithm in order to diminish as much as possible the impact of chattering behavior and thus achieving reliable and consistent stability by finding best values of gain G and the slope of sliding surface δ for (CSMCR) to ensure the stability of single inverted pendulum as a nonlinear system case study.…”

Performance Analysis and Optimization of a 6-DOF Robotic Crusher

“…New solutions are generated continuously by combining chromosomes. us, according to the fitness function, some chromosomes are selected in the new solutions to continue the combination until the best solution is finally found [23][24][25][26].…”

Structural Analysis and Application of Non-Standard Components Based on Genetic Algorithm

“…According to the actual working According to Figure 1, the general structure of the non-standard part-turret chuck loader is designed, and the key parts-fixed base, rotary base, and two flanges are extracted to design, and the related multi-objective mathematical model is established. The mathematical model parameters include: design variables, constraints, objective function [10]. Secondly, a GA algorithm is used to optimize the established mathematical model, and the optimization results are compared and optimized repeatedly, modeling, and simulation, as well as manufacturing and processing of real objects.…”