DIFFERENTIAL EVOLUTION FOR OPTIMIZATION OF PID GAIN IN ELECTRICAL DISCHARGE MACHINING CONTROL SYSTEM

ABSTRACT PID controller of servo control system maintains the gap between Electrode and workpiece in Electrical Dis- charge Machining (EDM). Capability of the controller is significant since machining process is a stochastic phenomenon and physical behaviour of the discharge is unpredictable. Therefore, a Proportional Integral Derivative (PID) controller using Differential Evolution (DE) algorithm is designed and applied to an EDM servo actuator system in order to find suitable gain parameters. Simulation results verify the capabilities and effectiveness of the DE algorithm to search the best configuration of PID gain to maintain the electrode position. Keywords: servo control system; electrical discharge machining; proportional integral derivative; con- troller tuning; differential evolution

Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization

Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Especially on hydraulic positioning system that is highly nonlinear and difficult to be controlled whereby PID parameters needs to be tuned to obtain optimum performance criteria. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the limit of change in particle velocity and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a good tuning method in the hydraulic positioning system

Simulation Model of Servo Motor by Using Matlab

The research aims to develop documented empirical data to obtain a high-accuracy and effective system according to a principal system as a model that represents the system for all expected cases and different working conditions. The current works are simulating a servo motor that works with specifications as a mathematical representation of it down to its representation with a transformation function. The simulation is done for different cases, the first is without a controller, and the other is an operation simulation with a conventional controller that is with a PID controller. The results, through response and accuracy, prove the preference of PID controller systems in the speed of response and high accuracy with the change or different conditions of the system, i.e., working with linear systems. A simulation is being conducted to verify the use of control systems to improve the performance of servo motors. Algorithms of control systems are developed according to designs based on prior experience. Speed and position control are the most common and used in many applications, which created the need to choose them. To overcome fluctuations and obtain a quick response and a high-precision system used, control systems, as the results proved. The research contribution is developing a design for the user control systems also checking them in simulation with the servo motor system using MATLAB. They test them in the servo motor control as well to test their performance experimentally

Design and Implementation of Novel Fractional-Order Controllers for Stabilized Platforms

As a servo system to isolate disturbance or track trajectory, stabilized platform requires high-quality control. However, conventional PID control fails to meet that requirement.In this paper, a new controller design scheme is proposed for stabilized platform based on fractional calculus. The designed controller is called fractional-order PID (FOPID) controller, which has two extra parameters compared to conventional PID controller. On one hand, it enables people have more degrees of freedom to design FOPID controller, on the other hand, its differential order and integral order provides more flexibility to tune the controller performance. Therefore, a design method of FOPID controller based on dynamic software modeling is presented. To obtain the idea controller’s parameters, the particle swarm optimization (PSO) bionic algorithm is used to optimize an objective function.In addition, software simulation platform and hardware experiment platform are built to design and test the FOPID controller. Finally, simulations and experimental results are included to show the effectiveness of the new control method

Integrated control mechanism of electrical discharge machining system for higher material removal rate

A servo control system in Electrical Discharge Machining (EDM) system is a control system with an appropriate control algorithm to position electrode on a particular distance from workpiece during machining process. The gap between the electrode and the workpiece is in the range of 10 – 50 μm. This ideal gap is achieved by applying an appropriate control algorithm to the servo control system of the EDM, and maintaining this gap will improve the Material Removal Rate (MRR) during the machining process. A considerable number of unique methods were proposed in the control algorithm in order to bring the electrode to the optimum position. This research proposes a new method called Integrated Control Mechanism (ICM) to improve the MRR of the EDM system. A rotary encoder is used as an additional mechanical sensor for the feedback control system in order to limit the electrode movement. Modelling of EDM is further investigated to predict the MRR parameter and optimization of electrode control position. A Neural Network system is used to predict MRR where Particle Swarm Optimization (PSO) and Differential Evolution (DE) are studied and simulated to optimize the Proportional Integral Derivative (PID) control parameters for the EDM system. Research conducted shows that the proposed Feed Forward Artificial Neural Network improves the accuracy of prediction in determining MRR by 2.92% and PID parameter optimization is successfully applied either using PSO or DE. The ICM is successfully implemented and the result shows that MRR is higher when compared to the normal machining process

Hybrid pitch angle controller approaches for stable wind turbine power under variable wind speed

The production of maximum wind energy requires controlling various parts of medium to large-scale wind turbines (WTs). This paper presents a robust pitch angle control system for the rated wind turbine power at a wide range of simulated wind speeds by means of a proportional–integral–derivative (PID) controller. In addition, ant colony optimization (ACO), particle swarm optimization (PSO), and classical Ziegler–Nichols (Z-N) algorithms have been used for tuning the PID controller parameters to obtain within rated stable output power of WTs from fluctuating wind speeds. The proposed system is simulated under fast wind speed variation, and its results are compared with those of the PID-ZN controller and PID-PSO to verify its effeteness. The proposed approach contains several benefits including simple implementation, as well as tolerance of turbine parameters and several nonparametric uncertainties. Robust control of the generator output power with wind-speed variations can also be considered a significant advantage of this strategy. Theoretical analyses, as well as simulation results, indicate that the proposed controller can perform better in a wide range of wind speed compared with the PID-ZN and PID-PSO controllers. The WT model and hybrid controllers (PID-ACO and PID-PSO) have been developed in MATLAB/Simulink with validated controller models. The hybrid PID-ACO controller was found to be the most suitable in comparison to the PID-PSO and conventional PID. The root mean square (RMS) error calculated between the desired power and the WT’s output power with PID-ACO is found to be 0.00036, which is the smallest result among the studied controllers