Advanced Computing Concepts And Techniques In Control Engineering


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Advanced Computing Concepts and Techniques in Control Engineering


Advanced Computing Concepts and Techniques in Control Engineering

Author: Michael J. Denham

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-06-29


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Computational concepts and techniques have always played a major role in control engineering since the first computer-based control systems were put into operation over twenty years ago. This role has in fact been accelerating over the intervening years as the sophistication of the computing methods and tools available, as well as the complexity of the control problems they have been used to solve, have also increased. In particular, the introduction of the microprocessor and its use as a low-cost computing element in a distributed computer control system has had a profound effect on the way in which the design and implementation of a control system is carried out and, to some extent, on the theory which underlies the basic design strategies. The development of interactive computing has encouraged a substantial growth in the use of computer aided design methods and robust and efficient numerical algorithms have been produced to support these methods. Major advances have also taken place in the languages used for control system implementation, notably the recent introduction of Ada'", a language whose design is based on some very fundamental computer science concepts derived and developed over the past decade. With the extremely high rate of change in the field of computer science, the more recent developments have outpaced their incorporation into new control system design and implementation techniques.

Algorithms and Architectures for Real-Time Control 1991


Algorithms and Architectures for Real-Time Control 1991

Author: P.J. Fleming

language: en

Publisher: Elsevier

Release Date: 2014-07-22


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Computer scientists have long appreciated that the relationship between algorithms and architecture is crucial. Broadly speaking the more specialized the architecture is to a particular algorithm then the more efficient will be the computation. The penalty is that the architecture will become useless for computing anything other than that algorithm. This message holds for the algorithms used in real-time automatic control as much as any other field. These Proceedings will provide researchers in this field with a useful up-to-date reference source of recent developments.

Ontologically Controlled Autonomous Systems: Principles, Operations, and Architecture


Ontologically Controlled Autonomous Systems: Principles, Operations, and Architecture

Author: George A. Fodor

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-11-27


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Kevin M. Passino When confronted with a control problem for complicated physical process, a control engineer usually follows a predetermined design procedure. This procedure often begins with the engineer seeking to understand the process and the primary control objectives. A simple example ofa control problem is an automobile "cruise control" that provides the automobile with the capability of regulating its own speed at a driver-specified set-point (e. g. , 55 mph). One solution to the automotive cruise control problem involves adding an electronic controller that can sense the speed of the vehicle via the speedometer and actuate the throttle position so as to regulate the vehicle speed at the driver-specified value. Such speed regulation must be accurate even if there are road grade changes, head-winds, or variations in the number of passengers in the automobile. After gaining an intuitive understanding of the plant's dynamics and establishing the design objectives, the control engineer typically solves the cruise control problem by using an established design procedure. In particular, this control engineering design methodology involves: 1. Modeling/understanding the plant, 2. Construction of a controller to meet specifications (such as stability, rise-time, overshoot, and steady state error), 3. Analysis to make sure that the system will meet the performance objectives (e. g. , we might use mathematical, simulation-based, or experimental analysis), and 4. Iterating on the design until it is possible to "commission" the control system.