This paper presents the design of an indirect adaptive feedback linearization (FBL)based control using dynamic neural networks (DNN) for full-car nonlinear electrohydraulic suspensions. Particle swarm optimization (PSO) algorithm is used in training the DNN to learn the dynamics of the system. A multi-loop, PSO-optimized proportional-integral-derivative (PID) control is implemented for the feed...

In this paper, we propose a PID parameter tuning of particle swarm optimization for multiobjective optimization characteristics of two regional power system PID controller design. By defining a comprehensive consideration of system output overshoot, rise time and the fitness function term steadystate error indicators, such as the ITAE, and in accordance with the performance requirements of the ...

This paper proposes the novel model order formulation scheme to design a discrete PID controller for higher order linear time invariant discrete systems. Modified PSO (MPSO) based model order formulation technique has used to obtain the successful formulated second order system. PID controller is tuned to meet the desired performance specification by using pole-zero cancellation and proposed de...

Application of fractional order PID (FOPID) controller to an automatic voltage regulator (AVR) is presented and studied in this paper. An FOPID is a PID whose derivative and integral orders are fractional numbers rather than integers. Design stage of such a controller consists of determining five parameters. This paper employs particle swarm optimization (PSO) algorithm to carry out the aforeme...

Gain tuning is very important in order to obtain good performances for a given controller. Contour tracking performance is mainly determined by the selected control gains of a position domain PID controller. In this paper, three popular evolutionary algorithms are utilized to optimize the gains of a position domain PID controller for performance improvement of contour tracking of robotic manipu...

This paper presents the development of an optimal self-tuning PID controller for vibration suppression of flexible manipulator structures using particle swarm optimization (PSO). A simulation environment characterizing the dynamic behavior of the flexible manipulator system was first developed using finite difference (FD) approach to acquire the input-output data of the system. The global searc...

A novel tuning method is proposed for the design of fuzzy PID controllers for multivariable systems. In the proposed method, a PID controller is expressed in terms of fuzzy rules, in which the input variables are the error signals and their derivatives, while the output variables are the PID gains. In this manner, the PID gains are adaptive and the fuzzy PID controller has more flexibility and ...

In this paper conventional PID controller provides satisfactory results, still inefficiency persists due to extreme nonlinear nature and uncertainty in the dynamics of the plant. So optimize the pid non linear behavior by Gravitational search algorithm and particle swarm optimization. The PID controller is the most common form of feedback. PID control issued at the lowest level; the multivariab...

In this paper, a real-valued genetic algorithm (RGA) and a particle swarm optimization (PSO) algorithm with a new fitness function method are proposed to design a PID controller for the Automatic Voltage Regulator (AVR) system. The proposed fitness function can let the RGA and PSO algorithm search a high-quality solution effectively and improve the transient response of the controlled system. T...

The interconnected systems is continually increasing in size and extending over whole geographical regions, it is becoming increasingly more difficult to maintain synchronism between various parts of the power system. This paper work presents an advanced adaptive Particle swarm optimization technique to optimize the SVC controller parameters for enhancement of the steady state stability & overc...