第三阶段是七十年代的大系统理论时期，着重解决生物系统、社会系统这样一些众多变量的大系统的综合自动化问题；方法是时域法为主；重点是大系统多级递阶控制；核心装置是网络化的电子计算机。 从控制论的观点看，人是巧妙，灵活的控制系统。它善于根据条件的变化而作出正确的处理。如何将人的智能应用于实际的自动控制系统中，这是个有重要意义的问题。七十年代开始，人们不仅解决社会、经济、管理、生态环境等系统问题，而且为解决模拟人脑功能，形成了新的学科----人工智能科学，这是控制论的发展前沿。计算机技术的发展为人工智能的发展提供了坚实的基础。人们通过计算机的强大的信息处理能力来开发人工智能，并用它来模仿人脑。在没有人的干预下，人工智能系统能够进行自我调节、自我学习和自我组织，以适应外界环境的变化，并作出相应的决策和控制。 科学在发展，控制论也在不断发展。所以“现代”两个字加在“控制理论”前面，其含义会给人误解的。实际上，我们讲的现代控制理论指的是五六十年代所产生的一些控制理论，主要包括： 用状态空间法对多输入多输出复杂系统建模，并进一步通过状态方程求解分析，研究系统的可控性、可观性及其稳定性，分析系统的实现问题； 用变分法、大（小）值原理、动态规划原理等求解系统的优控制问题；其中常见的优控制包括时间短、能耗少等等，以及它们的组合优化问题；相应的有状态调节器、输出调节器、跟踪器等综合设计问题； 优控制往往要求系统的状态反馈控制，但在许多情况下系统的状态是很难求得的，往往需要一些专门的处理方法，如卡尔曼滤波技术来求得。这些都是现代控制理论的范畴。 六十年代以来，现代控制理论各方面有了很大的发展，而且形成几个重要的分支课程，如线性系统理论，优控制理论，自适应控制理论，系统辩识理论，等等。 对控制系统一定要进行定量分析，否则就没有控制论；而要进行定量分析，就必须用数学模型来刻划描述系统，也即建立系统的数学模型，这是一个很重要的问题。 经典控制论中常用一个高阶微分方程来描述系统的运动规律，而现代控制论中采用的是状态空间法，就是用一组状态变量的一阶微分方程组作为系统的数学模型。这是现代控制理论与经典控制理论的一个重要区别。从某种意义上说，经典控制中的微分方程只能描述系统的输入与输出的关系，却不能描述系统内部的结构及其状态变量，它描述的只是一个‘黑箱’系统。而现代控制论中的状态空间法不但能描述系统输入与输出的关系，而且还能完全描述内部的结构及其状态变量的关系，它描述的是一个‘白箱’系统。由于能够描述更多的系统信息，所以可以实现更好的系统控制。 控制论、信息论、系统论作为独立的学科，各自都有自己的发展方向，同时又有内在的联系。在研究通讯和控制时，都离不开系统；研究系统或控制时，又离不开信息。一般系统论把其研究对象作为一个整体加以考虑，提出适合于一切系统的模式、原则和规律，强调系统于个体，这有助于说明有组织的系统。
The third stage is the period of large-scale system theory in the 1970s, which focuses on the comprehensive automation of large-scale systems with many variables such as biological systems and social systems; Time domain method is the main method; The emphasis is on multi-level hierarchical control of large-scale systems; The core device is a networked computer. From the viewpoint of cybernetics, man is the most ingenious and flexible control system. It is good at making correct treatment according to the change of conditions. How to apply human intelligence to practical automatic control system is a significant problem. Since the 1970s, people have not only solved the system problems of society, economy, management and ecological environment, but also formed a new discipline - Artificial Intelligence Science, which is the development frontier of cybernetics. The development of computer technology provides a solid foundation for the development of artificial intelligence. People develop artificial intelligence through the powerful information processing ability of computer, and use it to imitate the human brain. Without human intervention, the artificial intelligence system can conduct self-regulation, self-learning and self-organization to adapt to the changes of the external environment and make corresponding decisions and controls. Science is developing, and cybernetics is also developing. Therefore, if the word "modern" is added in front of "control theory", its meaning will be misunderstood. In fact, the modern control theory we are talking about refers to some control theories produced in the 1950s and 1960s, mainly including: modeling the multi input and multi output complex system with the state space method, further studying the controllability, observability and stability of the system through the solution and analysis of the state equation, and analyzing the implementation of the system; The optimal control problem of the system is solved by variational method, maximum (minimum) value principle and dynamic programming principle; The common optimal control includes the shortest time, the least energy consumption and so on, as well as their combination optimization problems; The corresponding integrated design problems include state regulator, output regulator and tracker; The optimal control often requires the state feedback control of the system, but in many cases, the state of the system is difficult to obtain, and it often needs some special processing methods, such as Kalman filter technology. These are the categories of modern control theory. Since the 1960s, various aspects of modern control theory have developed greatly, and several important branch courses have been formed, such as linear system theory, optimal control theory, adaptive control theory, system identification theory, and so on. Quantitative analysis must be carried out for the control system, otherwise there will be no cybernetics; For quantitative analysis, it is necessary to describe the system with mathematical model, that is, to establish the mathematical model of the system, which is a very important problem. In classical cybernetics, a higher-order differential equation is often used to describe the motion law of the system, while in modern cybernetics, the state space method is used, that is, a set of first-order differential equations of state variables are used as the mathematical model of the system. This is an important difference between modern control theory and classical control theory. In a sense, the differential equation in classical control can only describe the relationship between the input and output of the system, but can not describe the internal structure of the system and its state variables. It describes only a 'black box' system. The state space method in modern cybernetics can not only describe the relationship between system input and output, but also completely describe the internal structure and the relationship between its state variables. It describes a 'white box' system. Because more system information can be described, better system control can be achieved. Cybernetics, information theory and system theory, as independent disciplines, have their own development directions and internal relations at the same time. In the study of communication and control, it is inseparable from the system; When studying system or control, information is indispensable. The general system theory considers its research object as a whole, puts forward the models, principles and laws suitable for all systems, and emphasizes that the system is for the individual, which helps to explain the organized system.
客服1