Variable universe fuzzy control for vehicle semi-active suspension system with MR damper combining fuzzy neural network and particle swarm optimization

Improved Chaotic Quantum-Behaved Particle Swarm Optimization Algorithm for Fuzzy Neural Network and Its Application

“…To assess the performance of the proposed ICQPSO algorithm, six benchmark functions are examined, and statistical results are compared with PSO [13], SINPSO [17], APSO [18], QPSO [21], and HCQPSO [31,32]. QPSO and PSO are the basic traditional algorithms.…”

“…It is an effective way to improve the FNN performance by replacing the traditional learning algorithm by metaheuristic algorithms such as the particle swarm optimization (PSO) algorithm [13][14][15]. However, when the considered problem is a complex high-dimensional problem, PSO algorithm has the disadvantage of premature convergence [16][17][18][19].…”

Disturbance Rejection in a One‐Half Semiactive Vehicle Suspension by means of a Fuzzy-H∞ Controller

“…Wang et al [20] developed an optimized static output feedback controller and reduced by nearly 90% the maximum peak value registered for € Z s and € θ. Pang et al [24] implemented a variable universe fuzzy control with fuzzy neural networks and particle swarm optimization and reduced € Z s and € θ by approximately 39%, whereas suspension deflections (front and rear) were reduced by 33%. In addition, Benariba et al [49] developed a suspension with sliding mode control supplemented with Lyapunov surfaces and managed to reduce the Z s and θ by approximately 40%, while the deflection was reduced by 70%.…”

“…Results were generated in the frequency domain. In addition, Pang et al [24] developed a fuzzy controller for an experimental MR semiactive suspension based on neural networks and particle swarm optimization.…”

Design and Modeling for 2D Plate Type MR Damper

“…Compared to conventional hydraulic damper, the damping stiffness of MR damper can be changed using an embedded control system, which can produce a controllable magnetic field intensity by the coil placed on the piston. The MR damper was widely used in many fields, such as vehicle suspension systems Yu et al, 2017;Anwesa and Manas, 2018), clutches (Hema et al, 2017;Topcu et al, 2018), bridges and buildings (Mohammad and Amir, 2018) and the control systems for MR damper have been researched (Kang et al, 2018;Pang et al, 2018), by using control system, the damper can be easily controlled.…”