A system is called an intelligent control system if it has a perceptual environment, continuous access to information to reduce uncertainty, and the ability to plan, generate, and execute control actions. Intelligent control technology is constantly developing in the process of learning from the human brain. The human brain is a super intelligent control system with real-time reasoning, decision-making, learning and memory functions, which can adapt to various complex control environments.
 
　　Intelligent control is a kind of automatic control that can automatically drive intelligent machines to achieve their goals without human intervention. It is also an important field of computer simulation of human intelligence. Intelligent valve positioners are also one of them. Hydraulic transmission, as a muscle in the mechanical system, can play a more powerful function under the intelligent control of the system!
 
　　Automatic control combined with artificial intelligence
 
　　With the development of artificial intelligence and computer technology, it is possible to combine automatic control and artificial intelligence as well as some related disciplines in system science (such as systems engineering, systems science, operations research, information theory) to establish a suitable system for complex systems. Control theory and technology.
 
　　Intelligent control is produced under these conditions. It is the latest development stage of automatic control technology, and it is also the research field of computer simulation of human intelligence. In 1965, Fu Jingsun first proposed the use of heuristic inference rules of artificial intelligence for learning control systems. In 1985, the Intelligent Control Academic Symposium was held for the first time in the United States. In 1987, the first international academic conference on intelligent control was held in the United States, marking the recognition of intelligent control as a new branch of discipline.
 
　　Intelligent control has an analytical approach and characteristics that combines interdisciplinary and quantitative and qualitative.
 
　　Algorithmic solution
 
　　For many complex systems, it is difficult to establish effective mathematical models and use conventional control theory to perform quantitative calculations and analysis. It is necessary to use a combination of quantitative methods and qualitative methods. The purpose of combining quantitative methods with qualitative methods is to guide the solution process by the machine with human intelligence and experience.
 
　　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 real-world models, the identification of symbols and environments, and the knowledge base and inference engine. In development, the key issue of intelligent control is not to design a conventional controller, but to develop a model of an intelligent machine. In addition, the core of intelligent control is at the high level of control, that is, organizational control. High-level control is the organization, decision-making and planning of the actual environment or process to solve the problem. In order to accomplish these tasks, related technologies such as symbol information processing, heuristic programming, knowledge representation, automatic reasoning, and decision making are required.
 
　　These problem solving processes have certain similarities with the thinking process of the human brain, that is, they have a certain degree of "intelligence".