Classical Control Theory下载

weixin_39820780 2021-01-28 08:31:05

这是一本介绍自动控制原理的经典资料。介绍了典型的控制系统及其原理，非常适合作为入门读物。
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这是一本介绍自动控制原理的经典资料。介绍了典型的控制系统及其原理，非常适合作为入门读物。

The book is addressed to students inengineering who have had an undergraduate course in signals and systems, including an introduction to frequency-domain methods of analyzing feedback control systems, namely, Bode plots and the Nyquist criterion. A prior course on state-spacetheory would be advantageous for some optional sections, but is not necessary.To keep the development elementary,the systems are single-input/single-output and linear, operating in continuous time.

This textbook introduces the core concepts and results of Control and System Theory. Unique in its emphasis on foundational aspects, it takes a "hybrid" approach in which basic results are derived for discrete and continuous time scales, and discrete and continuous state variables. Primarily geared towards mathematically advanced undergraduate or graduate students, it may also be suitable for a second engineering course in control which goes beyond the classical frequency domain and state-space material. The choice of topics, together with detailed end-of-chapter links to the bibliography, makes it an excellent research reference as well.

无线通信系统中经典的功率控制博弈论算法matlab实现。 (The classical game theory algorithm of power control in wireless communication system is realized by MATLAB.)

Model Predictive Control：THEORY AND PRACTICE ABSTRACT We refer to Model Predictive Control (MPC) as that family of controllers in which there is a direct use of an explicit and separately identifiable model. Control design methods based on the MPC concept have found wide acceptance in industrial applications and have been studied by academia. The reason for such popularity is the ability of MPC designs to yield high performance control systems capable of operating without expert intervention for long periods of time. In this paper the issues of importance that any control system should address are stated. MPC techniques are then reviewed in the light of these issues in order to point out their advantages in design and implementation. A number of design techniques emanating from MPC, namely Dynamic Matrix Control, Model Algorithmic Control, Inferential Control and Internal Model Control, are put in perspective with respect to each other and the relation to more traditional methods like Linear Quadratic Control is examined. The flexible constraint handling capabilities of MPC are shown to be a significant advantage in the context of the overall operating objectives of the process industries and the 1-,2-, and 00 norm formulations of the performance objective are discussed. The application of MPC to non linear systems is not covered for brevity. Finally, it is explained that though MPC is not inherently more or less robust than classical feedback, it can be adjusted more easily for robustness.

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