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In this paper, a nonlinear semi-active vehicle suspension system using MR fluid dampers is investigated to enhance ride comfort and vehicle stability. Fuzzy logic and fuzzy self-tuning PID control techniques are applied as system controllers to compute desired front and rear damping forces in conjunction with a Signum function method damper controller to assess force track-ability of system controllers. The suggested fuzzy self-tuning PID operates fuzzy system as a PID gains tuner to mitigate the vehicle vibration levels and achieve excellent performance related to ride comfort and vehicle stability. The equations of motion of four-degrees-of-freedom semi-active half-vehicle suspension system incorporating MR dampers are derived and simulated using Matlab/Simulink software.

This paper introduces an optimum design for a feedback controller of a fully active vehicle suspension system using the combined multi-objective particle swarm optimization (CMOPSO) in order to minimize the actuator power consumption while enhancing the ride comfort. The proposed CMOPSO algorithm aims to minimize both the vertical body acceleration and the actuator power consumption by searching about the optimum feedback controller gains. A mathematical model and the equations of motion of the quarter-car active suspension system are considered and simulated using Matlab/Simulink software. The proposed active suspension is compared with both active suspension system controlled using the linear quadratic regulator (LQR) and the passive suspension systems. Suspension performance is evaluated in time and frequency domains to verify the success of the proposed control technique.

Proportional-integral-derivative (PID) controller is effective, popular and cost effective for a lot of scientific and engineering applications. In this paper, PID and fuzzy-self-tuning PID (FSTPID) controllers are applied to improve the performance of an active seat suspension system to enhance the pregnant woman comfort. The equations of motion of thirteen-degrees-of-freedom (13-DOF) active seat suspension system incorporating pregnant woman body model are derived and simulated. PID gains are tuned and estimated using genetic algorithm (GA) to formulate GA PID controller. In FSTPID, fuzzy logic technique is used to tune PID controller gains by selecting appropriate fuzzy rules using Matlab/Simulink software. Both controlled active seat suspension systems are compared with a passive seat suspension. Suspension performance is evaluated under bump and random road excitations in order to verify the success of the proposed controllers.

In this paper, a fuzzy-PID controller is applied in a half vehicle active suspension system to enhance vibration levels of vehicle chassis and passenger seat. The fuzzy-PID controller consists of fuzzy and PID connecting in a series manner, the fuzzy output is considered as the PID input. Genetic Algorithm (GA) is selected to tune controller parameters to obtain optimal values that minimize the objective function. The equations of motion of five-degrees-of-freedom active half-vehicle suspension system are derived and simulated using Matlab/Simulink software. Double bumps and random road excitations are used to study the performance of suspension systems including bounce and pitch motion. The performance of the active suspension system using optimized fuzzy-PID controller is compared with conventional passive to show the efficiency of the proposed active suspension system.

Proportional integral derivative (PID) control method is an effective, easy in implementation and famous control technique applied in several engineering systems. Also, Genetic Algorithm (GA) is a suitable approach for optimum searching problems in science, industrial and engineering applications. This paper presents the usage of GA for determining the optimal PID controller gains and their implementation in the active quarter-vehicle suspension system to achieve good ride comfort and vehicle stability levels. The GA is applied to solve a combined multi-objective (CMO) problem to tune PID controller gains of vehicle active suspension system for the first time. The active vehicle suspension system is modeled mathematically as a two degree-of-freedom mechanical system and simulated using Matlab/Simulink software.

Nonparametric models do not require any assumptions on the underlying input/output relationship of the system being modeled so that they are highly useful for studying and modeling the nonlinear behaviour of Magnetorheological (MR) fluid dampers. However, the application of these models in semi-active suspension is very rare and most theoretical works available on this topic address the application of parametric models (e.g. Modified Bouc-Wen model). In this paper, a nonparametric MR damper model based on the Restoring Force Surface technique is applied in vehicle semi-active suspension system. It consists of a three dimensional interpolation using Chebyshev orthogonal polynomial functions to simulate the MR damper force as a function of the displacement, velocity and input voltage. Also, a damper controller based on a Signum function method is proposed, for the first time, for use in conjunction with the system controller of a semi-active vehicle suspension.