Modelling and Simulation for Industrial DC Motor Using Intelligent Control

AbstractThis paper presents an overview of Proportional Integral control (PI) and Artificial Intelligent control (AI) algorithms. AI and PI controller are analyzed using Matlab [Simulink] software. The DC motor is an attractive piece of equipment in many industrial applications requiring variable speed and load characteristics due to its ease of controllability. The main objective of this paper illustrates how the speed of the DC motor can be controlled using different controllers. The simulation results demonstrate that the responses of DC motor with an AI control which is Fuzzy Logic Control shows satisfactory well damped control performance. The results shows that Industrial DC Motor model develop using its physical parameters and controlled with an AI controller give better response, it means it can used as a controller to the real time DC Moto

Modified Predictive Control for a Class of Electro-Hydraulic Actuator

Many model predictive control (MPC) algorithms have been proposed in the literature depending on the conditionality of the system matrix and the tuning control parameters. A modified predictive control method is proposed in this paper. The modified predictive method is based on the control matrix formulation combined with optimized move suppression coefficient. Poor dynamics and high nonlinearities are parts of the difficulties in the control of the Electro-Hydraulic Actuator (EHA) functions, which make the proposed matrix an attractive solution. The developed controller is designed based on simulation model of a position control EHA to reduce the overshoot of the system and to achieve better and smoother tracking. The performance of the designed controller achieved quick response and accurate behavior of the tracking compared to the previous study