What is smart control
Intelligent controls (intelligent controls) is an automatic control technology that can autonomously drive intelligent machines to achieve control goals without human intervention. For many complex systems, it is difficult to establish effective mathematical models and use conventional control theories to carry out quantitative calculations and analysis, and a control method that combines quantitative and qualitative methods must be adopted.
The purpose of the combination of quantitative and qualitative methods is to use human-like wisdom and experience to guide the solution process. Therefore, when researching and designing intelligent systems, the main focus is not on the expression, calculation and processing of mathematical formulas, but on the description of tasks and realistic models, the recognition of symbols and environments, and the knowledge of knowledge bases and inference engines. In terms of development, the key issue of intelligent control is not to design conventional controllers, but to develop models of intelligent machines.
In addition, the core of intelligent control lies in high-level control, that is, organizational control. High-level control is the organization, decision-making and planning of the actual environment or process in order to solve the problem. In order to accomplish these tasks, it is necessary to adopt related technologies such as symbolic information processing, heuristic programming, knowledge representation, automatic reasoning and decision-making. The process of solving these problems is similar to the thinking process of the human brain, that is, it has a certain degree of "intelligence".
With the development of artificial intelligence and computer technology, it has become possible to combine automatic control, artificial intelligence, and some related disciplines in system science (such as systems engineering, systems science, operations research, and information theory) to establish a system suitable for complex systems. Control theory and technology. Intelligent control is produced under this condition. It is the latest development stage of automatic control technology, and it is also a research field in which computers are used to simulate human intelligence for control.
Intelligent control is based on control theory, computer science, artificial intelligence, operations research and other disciplines, and expands related theories and technologies. Among them, fuzzy logic, neural networks, expert systems, genetic algorithms and other theories and adaptive Control, self-organizing control, self-learning control and other technologies.
The difference between intelligent control and traditional control
The consensus in the control community in recent years is that the design of the controller is viewed from the level of information science, and its core is the design of the control algorithm. The control algorithm is mainly based on the input and output information of the system, the system and the information that may change, and the system working environment. The information, as well as the information on the tasks and requirements of the system, are collected, processed, analyzed, and calculated to form control commands that the system can accept and can work accordingly. The formation of control commands is the completeness of the information needed to form the commands. The first is the cognition of the control object, that is, the modeling of the system, and the recognition of a series of information such as input, output, environmental changes, etc. Knowing all involves the collection and processing of information, the transmission of information, and so on. Regardless of the information preparation required for the formation of control commands such as modeling, or the process of forming control commands after the information is relatively complete, all kinds of computer algorithms must be effective. These algorithms can be traditional or intelligent due to the characteristics of the problem, which naturally depends on the specific conditions and requirements of using these algorithms.
Traditional automatic control is based on a definite model, while the research object of intelligent control has serious uncertainty in the model, that is, the structure and parameters of the model are unknown or poorly understood in a large range. For example, the ill-conditioned structure of the industrial process and the unpredictability of certain disturbances make it impossible to establish a model. These problems are difficult to solve for traditional model-based automatic control.
Traditional control theory has more mature theories for linear problems, and although there are some nonlinear methods that can be used for highly nonlinear control objects, they are not satisfactory. And intelligent control has found a way out for solving such complex nonlinear problems, and has become an effective way to solve such problems. In addition to the above-mentioned characteristics, industrial process intelligent control systems have other characteristics. For example, the controlled objects are often dynamic, and the control system moves online, and generally requires high real-time response speed. It is precisely these characteristics that It determines the difference between it and other intelligent control systems such as intelligent robot system, aerospace control system, transportation control system, etc., determines its control method and the uniqueness of its form.
It is very inconvenient to exchange information between the input or output equipment of the traditional automatic control system and the human and the external environment. It is hoped to create an information input device that can accept printed, graphic, or even handwritten and oral commands, which can be more in-depth and flexible. The system communicates information, and at the same time expands the capacity of the output device, which can output information in the form of text, drawings, three-dimensional images, and language. In addition, ordinary automatic devices cannot accept, analyze, and perceive various visible and audible images, combinations of sounds, and other external conditions. In order to expand the information channel, it is necessary to install precise sound transmitters that can mechanically simulate various sensations, that is, text, sound, and object recognition devices. Fortunately, the rapid development of computer and multimedia technology in recent years has provided material preparations for the development of intelligent control in this area, turning intelligent control into a multi-directional "three-dimensional" control system.
Compared with traditional automatic control systems, intelligent control systems have sufficient knowledge about human control strategies, controlled objects and the environment, and the ability to use these knowledge; intelligent control systems can be represented by knowledge-based non-mathematical generalized models and The mathematically expressed hybrid control process adopts a multi-modal control method combining open and closed loop control and qualitative and quantitative control; the intelligent control system has compensation and self-repair capabilities and judgment and decision-making capabilities. Intelligent control adopts a completely new idea. It adopts a human way of thinking, establishes a logical model, and uses a control method similar to the human brain to control.
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