Satean Tunyasrirut

Implementation of a dSPACE DSP-based state feedback with state observer using Matlab/Simulink for a speed control of DC motor system

This paper presents design and implements the state feedback controller to design using Matlab/simulink for a speed control system of DC motor. The proposed controller will be a state feedback with state observer controller incorporating integrator. The controller design by pole placement technique is also introduced to the system for regulates and tracking speed response. The overall control system is implemented on dSPACE DSP DS1104 controller board. This scheme leads to be able to adjust the speed of the motor by control the input voltage of power amplified. The experimental results in testing the 48 watt DC motor system from no load condition to rated condition show the effectiveness of the proposed control scheme. It is found that the motor speed can be controlled to be constant in the operating range of 0-3200 rpm at no load and full load.

Phase control thyristor based soft-starter for a grid connected induction generator for wind turbine system

This paper presents a power thyristors based soft starter strategy for an induction-generator based wind turbine system. Soft-starter is designed to reduce inrush current or surge in current while achieving a proper synchronism between the generator and the grid. The designed soft-starter successfully limits the high inrush current during the connection of the wind-turbine system to the grid. An experimental investigation is done to find out suitable values of the power thyristor for soft-connection of a wind turbine system with the grid. Tests are carried out on a three phase induction generator, based system controller and relays for the system connection/disconnection from the grid. This paper describes the soft-starting principle, the designed soft-starter, application of the soft-starter in wind power generation, and experimental test results.

Implementation of a Scalar Controlled Induction Motor Drives

This paper presents design and implements a V/F control speed of induction motor. This scheme leads to be able to adjust the speed of the motor by control the frequency and amplitude of the stator voltage, the ratio of stator voltage to frequency should be kept constant, which is known as V/F or scalar control. The PI controller is applied to speed signal model of the inverter and is then downloaded to dSPACE through Simulink. The experimental results are analyzed and compared simulation in testing the 0.22 kW induction motor from no-load condition to rated condition, its found that the motor speed to be constant when the load varies, as shown the effectiveness of the proposed control scheme

Comparison power quality of the voltage source inverter type SVPWM and SPWM technique for induction motor drive

This paper presents the comparison power quality of the voltage source inverter type a space vector pulse width modulation (SVPWM) and sinusoidal pulse width modulation (SPWM) technique for adjust speed of the induction motor. All the drives are implemented on real-time Simulink model of three phase variable magnitude of voltage and variable frequency type are used the drive voltage source inverter system. This scheme leads to be able to adjust the speed of the motor by control the frequency and amplitude of the model. The ratio of input stator voltage to frequency should be kept constant. The overall control system is implemented on dSPACE DSP DS1104 controller board. The power quality of voltage source inverter are measured and compared to supply the 120 watt induction motor full load condition.

Level Control in Horizontal Tank by Fuzzy Logic Controller

This paper proposes a design fuzzy logic controller to control the water level in horizontal tank which has diameter 300 mm, long 480 mm, and total volume 33.9 litters. The proposed controller is implemented on a microcontroller MCS-51 by using C language. The performance of the system can be improved even when step inputs is used. The rise time and steady state error of the process response are considered. From the experiment results found that the proposed controller can be effectively used for controlling the level in horizontal tank with and without interrupt load accurately

PSO-Based Optimal PI(D) Controller Design for Brushless DC Motor Speed Control with Back EMF Detection

This paper proposes a design of optimal PI(D) controller for brushless DC (BLDC) motor speed control by the particle swarm optimization (PSO), one of the powerful metaheuristic optimization search techniques. The proposed control system is implemented on the TMS320F28335 DSP board interfacing to MATLAB/SIMULINK. With Back EMF detection, the proposed system is considered as a class of sensorless control. This scheme leads to the speed adjustment of the BLDC motor by PWM. In this work, the BLDC motor of 100 watt is conducted to investigate the control performance. As results, it was found that the speed response of BLDC motor can be regulated at the operating speed of 800 and 1200 rpm in both no load and full load conditions. Very satisfactory responses of the BLDC system can be successfully achieved by the proposed control structure and PSO-based design approach.

Application of Intensified Current Search to Optimum PID Controller Design in AVR System

The intensified current search (ICS) is one of the newest metaheuristic optimization search techniques for solving the continuous optimization problems. It is the latest modified version of the original current search (CS). In this paper, the algorithms of the ICS is proposed and the performance evaluation of the ICS is investigated via five well-known surface optimization problems. The ICS is then applied to design an optimum PID controller for the AVR widely used in power systems. Based on the optimization context, the sum of absolute errors between reference input and output response of the system is performed as the objective function to be minimized. This paper demonstrates how to conduct the ICS to search efficiently the optimum PID controller parameters of the AVR system. As results, the optimum PID controller for the AVR system is successfully and rapidly obtained by the ICS. Moreover, the ICS-based design approach performs high robustness once parameter variations are occurred in the control loop.

2-DOF Smith predictor control system design by root locus technique

Smith predictor control is theoretically a good solution to the problem of controlling the time delay systems. However, there are few control design method of Smith predictor scheme for obtain the desired transient and steady state responses arbitrary. In this paper we present a design method of 2-DOF Smith predictor control system design by root locus technique for achieve in the closed loop system performance of stable processes. The simulation results of the control system compared with those using Smith predictor tuned by the Ziegler-Nicholspsila second method and internal model control (IMC) design method will also be demonstrated.

Mathematical modelling and simulation of phase advance angle for Brushless DC motor

The brushless DC motor is widely used in various industrial fields because of low maintenance, high power density and high efficiency. The permanent magnets in the rotor generate a constant magnetic flux which is limited by the motor speed range. Mathematical modelling of brushless DC motor is necessary for realizing the dynamic behaviour. This paper presents a phase advanced angle for brushless DC motor to extend speed range of brushless DC motor beyond the rate top speed. The experimental designed system is simulated. The simulated results show that a phase advanced angle in the designed system can extend speed range. Finally, it can improve the ability of the proposed system, efficiently.

Hourly load forecasting of power system over Northeastern Thailand using artificial neural network

Thailand has limited resources to generate the electric power. In developing countries, the electrical demand is growing continuously. Power system planning is very important issues. There are three major components of the electrical power system namely, generation, a high voltage transmission line, and a distribution system. The hourly power variables, at Bamnet Narong substation in northeastern Thailand is fed to artificial neural network models for the short-term load forecasting. The training dataset in ANN is from measurement data of Supervisory Control and Data Acquisition (SCADA) system such as true power, reactive power and voltage source. The training methods with optimized weights in the ANNs, Levenberg-Marquart algorithm (LMA) and Gradient Descent algorithm (GDA), are applied. The results have shown that the ANN with LMA is more effective than GDA.