DESIGN OF FUZZY PID CONTROLLER FOR SPEED CONTROL OF BLDC MOTOR PHASE I REPORT Submitted by ARJUN M Register No. 710012428003 in partial fulfilment for the award of the degree of MASTER OF ENGINEERING in CONTROL AND INSTRUMENTATION DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING ANNA UNIVERSITY REGIONAL CENTRE‚ COIMBATORE COIMBATORE-641 047 DECEMBER 2013 ii ANNA UNIVERSITY REGIONAL CENTRE‚ COIMBATORE COIMBATORE-641 047 DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING PROJECT WORK
Premium Electric motor Control theory PID controller
Assignment Week 2 APP-44 Game Controllers: Enriching the Gaming Experience Harley Kimble Longherst University
Premium Wii Video game Input device
the GA-PID and ACO-PID controllers for a 3-phase 60KW SRM motor which are implemented & simulated by using Matlab-Simulink software program. Motor parameters used for simulation are given in Table 1. Tables 2 and 3 shows the GA-PID and ACO-PID controller’s parameters. the response of Kp‚ Ki and Kd parameters are summarized on table 4 which shows that the proportional controller “Kp” will have the effect of reducing rise time and will reduce the steady state error while the integral controller “Ki”
Premium PID controller Control theory Control engineering
control the position of the ball on the beam. The ball rolls on the beam freely. By employing linear sensing techniques‚ the information from the sensor can be taken and compared with desired positions values. The difference can be fed back into the controller‚ and then into the motor in order to gain the desired position. The mathematical model for this system is inherently nonlinear but may be linear around the horizontal region. This simplified linear model‚ however‚ still represents many typical
Premium Control theory PID controller
Expert Systems with Applications Expert Systems with Applications 32 (2007) 911–918 www.elsevier.com/locate/eswa Brain emotional learning based intelligent controller applied to neurofuzzy model of micro-heat exchanger Hossein Rouhani a‚*‚1‚ Mahdi Jalili b‚2‚ Babak N. Araabi b‚ Wolfgang Eppler c‚ Caro Lucas b b a Mechanical Engineering Department‚ University of Tehran‚ Tehran‚ Iran Control and Intelligent Processing Center of Excellence‚ Electrical and Computer Engineering Department
Premium Control theory Control engineering PID controller
taking from the Pittman S232S003 DC data sheet. The system parameters are expressed below in Table 1. Table 1: System Parameters for Servomotor (with friction‚ non-linear) Velocity Control: 1A. In Figure 3‚ we implemented a proportional controller (Kp) and used the model to determine the motor velocity‚ wm‚ as a function of time for a Vd = 2V u(t). Table 1-2 below summarizes the systems parameters used for this analysis‚ and the results for this process can be seen in Table 2. Table 1-2:
Premium Control theory PID controller Control engineering
feedback control - 8.1 8. FEEDBACK CONTROL SYSTEMS Topics: • Transfer functions‚ block diagrams and simplification • Feedback controllers • Control system design Objectives: • To be able to represent a control system with block diagrams. • To be able to select controller parameters to meet design objectives. 8.1 INTRODUCTION Every engineered component has some function. A function can be described as a transformation of inputs to outputs. For example it could be an amplifier that
Premium Control theory PID controller Feedback
Instrumentation and Measurement Laboratory AEAV-312 Exp No: - 01 Exp Name: - Water Level Control by Feedback Method. Objectives: The Objective of this experiment is to control the level water by feedback transducer‚ and get familiar with the action of PID. Theory: Measurement of level and pressure (analog type output) with pressure and level measurements‚ the pressure sensor set at the bottom of the vertical column of unit ty3oa/ev is used. Definition of an Analog Variable: An analog measurement
Premium Control theory Measurement Pressure
Reconnaissance (IFOR) is an autonomous aerial vehicle that has been developed by BITS Pilani Dubai Campus students. The vehicle is capable of localizing itself using the SLAM algorithm‚ stabilize its attitude (pitch‚ roll and yaw) and altitude using PID controllers‚ plan paths around obstacles and navigate an unknown indoor environment with wall following guidance. In addition‚ it has been designed to be capable of pattern recognition which would enable it to recognize images and signs. These features enable
Premium PID controller Control theory
indirectly a frequency control depending upon 2 to 3% of droop setting of the generator. Secondary loop control is done by a PID controller‚ as it accounts 2% frequency drop. It is the role of secondary controller to eliminate the frequency deviation and the tie line power variation when subjected to unit step load disturbances. There are several methods for tuning a PID controller. The most effective methods generally involves the development of some form of process model‚ and then choosing P‚I and
Premium Control theory PID controller Control system