Microcomputer Based Adaptive Control Applied To Thyristor Driven Dc Motors

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.

The workshop brought together international experts in the field of robust adaptive control to present recent developments in the area. These indicated that the theory of adaptive control is moving closer to applications and is beginning to give realistic guidelines useful in practical situations. The proceedings also focused on the value of such practical features as filtering, normalization, deadzones and unification of robust control and adaptation.

As the use and relevance of robotics for countless scientific purposes grows all the time, research into the many diverse elements of the subject becomes ever more important and in demand. This volume examines in depth the most topical, complex issues of modelling and identification in robotics. The book is divided into three main parts. The !first part is devoted to robot dynamics modelling and identification of robot and load parameters, incorporating friction torques, discussing identification schemes, and presenting simulations and experiment al results of robot and load dynamic parameters identification. A general concept of robot programming language for research and educational purposes is examined and there is a detailed outline of its basic structures along with hardware requirements, which both constitute an open robot controller architecture. Finally a hybrid controller is derived, and several experimental results of this system are outlined. This impressive discussion of the topic covers both the theoretical and practical, illustrated throughout by examples and experimental results, and will be of value to anyone researching or practising within the field of robotics, automation and system i dentification or to control engineers.

A FY 2001 Center Director's Discretionary Fund task to develop a test platform for the development, implementation. and evaluation of adaptive and other advanced control techniques for brushless DC (BLDC) motor-driven mechanisms is described. Important applications for BLDC motor-driven mechanisms are the translation of specimens in microgravity experiments and electromechanical actuation of nozzle and fuel valves in propulsion systems. Motor-driven aerocontrol surfaces are also being utilized in developmental X vehicles. The experimental test platform employs a linear translation stage that is mounted vertically and driven by a BLDC motor. Control approaches are implemented on a digital signal processor-based controller for real-time, closed-loop control of the stage carriage position. The goal of the effort is to explore the application of advanced control approaches that can enhance the performance of a motor-driven actuator over the performance obtained using linear control approaches with fixed gains. Adaptive controllers utilizing an exact model knowledge controller and a self-tuning controller are implemented and the control system performance is illustrated through the presentation of experimental results.Gwaltney, D. A.Marshall Space Flight CenterDIGITAL SYSTEMS; CONTROL SYSTEMS DESIGN; ADAPTIVE CONTROL; ELECTRIC MOTORS; ACTUATORS; PROPORTIONAL CONTROL; MATHEMATICAL MODELS; FEEDBACK CONTROL; REAL TIME OPERATION; ELECTROMECHANICAL DEVICES; PROPULSION SYSTEM PERFORMANCE; LINEARITY; FUEL VALVES

In this book, modeling and control design of electric motors, namely step motors, brushless DC motors and induction motors, are considered. The book focuses on recent advances on feedback control designs for various types of electric motors, with a slight emphasis on stepper motors. For this purpose, the authors explore modeling of these devices to the extent needed to provide a high-performance controller, but at the same time one amenable to model-based nonlinear designs. The control designs focus primarily on recent robust adaptive nonlinear controllers to attain high performance. It is shown that the adaptive robust nonlinear controller on its own achieves reasonably good performance without requiring the exact knowledge of motor parameters. While carefully tuned classical controllers often achieve required performance in many applications, it is hoped that the advocated robust and adaptive designs will lead to standard universal controllers with minimal need for fine tuning of control parameters.