IJERT-Position Control of Servo Systems using PID Controller Tuning with Soft Computing Optimization Techniques (original) (raw)
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Tuning of PID Controller for Position Control of DC Servo Motor using Luus-Jaakola Optimization
— This paper presents an efficient and fast tuning method of controller parameters for position control of DC servo motor. A control scheme for PID controller tuning is proposed here which is based on Luus-Jaakola Optimization. Luus-Jaakola optimization procedure is used to optimize large scale nonlinear optimization problems. The tuning of PID controllers is accomplished by minimizing the Integral-Square-Error (ISE). The ISE is minimized using the Luus–Jaakola (LJ) optimization algorithm. LJ optimization procedure is a simple, yet powerful method for optimization available in literature. The results of PID control using LJ method are compared with the Ziegler-Nichol's (ZN) tuning. The simulation results show that the LJ method performs better results than the ZN technique and can successfully be used for tuning of PID controllers for DC servo motor. Keywords— Luus Jaakola (LJ), DC servo motor, Integral-Square Error (ISE), Ziegler-Nichols(ZN)
Tuning of PID Controller for DC Servo Motor using Genetic Algorithm
The position control study of DC servo motors is very important since they are extensively deployed in various servomechanisms. Normally PID controllers are used to improve the transient response of DC servo motors. At present, most tuning methods are designed to provide workable initial values, which are then further manually optimized for a specific requirement. This paper presents a flexible and fast tuning method based on genetic algorithm (GA) to determine the optimal parameters of the PID controller for the desired system specifications. Simulation results show that a wide range of requirements are satisfied with the proposed tuning method.
Position Control Of Dc Motor Using Advanced Soft Computing Technique
The aim of this paper is to design a position controller of a DC motor by selection of a PID parameters using BFOA. The model of a DC motor is considered as a third order system. And this paper compares two kinds of tuning methods of parameter for PID controller. One is the controller design by the BFOA second is the controller design by the Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the BFOA is better than the Ziegler & Nichols' method. The proposed method could be applied to the higher order system also.
Tuning PID Controller for Speed Control of DC Motor Using Soft Computing Techniques-A Review
2014
This paper presented a review study of tuning of Proportional Integral Derivative (PID) Controller for speed control of DC motor using soft computing techniques. DC motor is widely used in industries even if its maintenance cost is higher than the induction motor. Speed control of DC motor is attracted considerable research and several methods are evolved. The PID controller is the very commonly used compensating controller which is used in nonlinear systems. This controller is widely used in many different areas like aerospace, process control, manufacturing, automation etc. The tuning of PID parameter is very difficult. There are various soft computing techniques which are used for tuning of PID controller to control the speed control of DC motor. Tuning of PID parameters is important because these parameters have a great effect on the stability and performance of the control system.
Tuning of PID controller parameters is an important problem in control field. To solve this problem we used an Advanced Particle Swarm Optimization which is powerful stochastic evolutionary algorithm that is used to find the global optimum solution in search space. The proposed method has fast searching speed compared to standard PSO. Furthermore this method accelerates the convergence. However, it has been observed that the standard PSO algorithm has premature and local convergence phenomenon when solving complex optimization problem. This new algorithm is proposed to augment the original PSO searching speed. The optimum tuned PID controller is applied to a DC motor. The simulation results show that the PID controller designed by APSO demonstrates better results than GA, PSO and even Improved PSO technique.
PID PARAMETERS OPTIMIZATION USING ADAPTIVE PSO ALGORITHM FOR A DCSM POSITION CONTROL
This paper demonstrates a novel algorithm in particle swarm optimization, which is called Adaptive PSO (APSO), to optimize the gains of a proportional-integral-derivative (PID) controller concurrently to control the position of a DC servomotor (DCSM). The parameters of the PID controller (K P , K i , and K D ) are obtained, firstly, by using Ziegler-Nichols tuning method, secondly by using standard PSO algorithm, thirdly by using MPSO algorithm, and finally by using APSO algorithm. The transient response analysis has been done by comparing the performance of the four tuning methods. The results showed that the proposed algorithm gives better performance than the other optimization algorithms, and the DCSM reached very fast to the final position. The analysis and simulations have been made in MATLAB R2010a software environment.
Position control of DC motor using genetic algorithm based PID controller
Proceedings of the World Congress on …, 2009
The aim of this paper is to design a position controller of a DC motor by selection of a PID parameters using genetic algorithm. The model of a DC motor is considered as a third order system. And this paper compares two kinds of tuning methods of parameter for PID controller. One is the controller design by the genetic algorithm, second is the controller design by the Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the genetic algorithm is better than the Ziegler & Nichols' method. The proposed method could be applied to the higher order system also.