Recently, fractional-order proportional-integral-derivative (FOPID) controllers are demonstrated as a general form of the classical proportional-integral-derivative (PID) using fractional calculus. In FOPID controller, the orders of the derivative and integral portions are not integers which offer more flexibility in succeeding control objectives. This paper proposes a multi-objective genetic algorithm (MOGA) to optimize the FOPID controller gains to enhance the ride comfort of heavy vehicles. The usage of magnetorheological (MR) damper in seat suspension system provides considerable benefits in this area. The proposed semi-active control algorithm consists of a system controller that determines the desired damping force using a FOPID controller tuned using a MOGA, and a continuous state damper controller that calculates the input voltage to the damper coil. A mathematical model of a six degrees-offreedom seat suspension system incorporating human body model using an MR damper is derived and simulated using Matlab/Simulink software. The proposed semi-active MR seat suspension is compared to the classical PID, optimum PID tuned using genetic algorithm (GA) and passive seat suspension systems for predetermined chassis displacement. System performance criteria are examined in both time and frequency domains, in order to verify the success of the proposed FOPID algorithm. The simulation results prove that the proposed FOPID controller of MR seat suspension offers a superior performance of the ride comfort over the integer controllers.

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This paper describes the design and practical implementation for speed Fuzzy Self Tuning of Optimal PID control FSTOPID on a Servo Permanent Magnet Synchronous Motor PMSM. In this work, an industrial PMSM system has been identified including its drive. Nonlinear Least Squares Algorithm NLSA is used for model identification. For speed control, a variable load for the PMSM represents nontraditional control problem. One of the solutions to the problem is to apply a FSTOPID controller. This requires reformulating the control problem to include two parts, optimal PID controller and fuzzy logic controller FLC parts. The first part deals with the PID controller tuned using Ant Colony System ACS algorithm. The second one represents the on line fuzzy self-tuned of the optimal PID. The goal of this design is to regulate the speed and improve the transient performance of the PMSM system under load demand variations. Comparative analyses of practical implementation for the PMSM drive system are demonstrated under diverse load. Finally, experimental results show accurate identification and speed favorable performance. The results prove that the proposed controller is very useful for industrial servo PMSM system.