Microcomputer-Based Adaptive Control Applied to Thyristor-Driven DC-Motors

Microcomputer-Based Adaptive Control Applied to Thyristor-Driven DC-Motors
Author: Ulrich Keuchel
Publisher: Springer Science & Business Media
Total Pages: 166
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 1447120760

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computing methods, applications, philosophies, . . . , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The autotune method of Astrom and Hagglund had a major impact on the hardware and structure of PID process controllers. However, despite a substantial body of theoretical analysis, progress in transferring the benefits of more general self-tuning methods to industrial devices and processes has been much slower. This volume by Dr's Stephan and Keuchel shows that this type of technology transfer can be achieved and that the more advanced adaptive controllers do give performance benefits over conventional industrial (three term) controllers. The volume also shows the requirements in hardware, the need for software skills and the engineering techniques required to achieve satisfactory results. We hope that by recording their engineering know-how more researchers and industrialists will be encouraged to tap the benefits of advanced self-tuning and adaptive control methods. July, 1993 Michael J. Grimble and M. A. Johnson, Industrial Control Centre, Glasgow, Scotland, U. K.

DC Motor Control Using Real-Time Linux

DC Motor Control Using Real-Time Linux
Author: Asim Zaman
Publisher: LAP Lambert Academic Publishing
Total Pages: 76
Release: 2012
Genre:
ISBN: 9783659304552

System Control using Embedded systems or DSP kits can by no means match the user friendly nature of the computer. I am interfacing a hardware that is, in my case, a dc motor and is controlling its operational speed through the software. All the processing is done by the computer in Real Time and to introduce changes in the system's performance is just finger tips away. The use of computers in this project has acquired me the ease of control and greater accuracy. The computer is prepared to do the task by having a Red Hat Linux(r) with a Real-Time kernel installed. The computer ports do the necessary communication with the hardware. The source code running on the computer translates the data input into an instruction executed on the hardware. And the motor speed changes according to the duty cycle entered by the user and according to the need of the application in which the motor is being used. All one needs is some old fashioned computer, a dc motor and some motor drive circuitry to getting started. The whole set up costs a little, is efficient and user friendly. I guess automation has never been dreamed this much easy befor

DC Motor Speed Control with the Precence of Input Disturbance using Neural Network Based Model Reference and Predictive Controllers

DC Motor Speed Control with the Precence of Input Disturbance using Neural Network Based Model Reference and Predictive Controllers
Author: Mustefa Jibril
Publisher: GRIN Verlag
Total Pages:
Release: 2020-05-11
Genre: Computers
ISBN: 3346164179

Academic Paper from the year 2020 in the subject Computer Science - Miscellaneous, , language: English, abstract: In this paper we describe a technical system for DC motor speed control. The speed of DC motor is controlled using Neural Network Based Model Reference and Predictive controllers with the use of Matlab/Simulink. The analysis of the DC motor is done with and without input side Torque disturbance input and the simulation results obtained by comparing the desired and actual speed of the DC motor using random reference and sinusoidal speed inputs for the DC motor with Model Reference and Predictive controllers. The DC motor with Model Reference controller shows almost the actual speed is the same as the desired speed with a good performance than the DC motor with Predictive controller for the system with and without input side disturbance. Finally the comparative simulation result prove the effectiveness of the DC motor with Model Reference controller.