The classical control methods have shortcoming,, such as its fixed parameters, with a limited control effect, and the Biological Intelligence Algorithm provides a new way to break the bottleneck of the classical control methods because of its adaptive and learning mechanism. With the improvement of the theory of the reinforcement learning and the deep learning, the performance of the Biological Intelligence Algorithm is greatly improved. This paper reviews seven kinds of intelligent algorithms commonly used in intelligence control, and the application examples of combining the classical automatic control methods and the intelligent algorithms, especially, the reinforcement learning. The development status and the future development trend of the intelligent control based on the reinforcement learning, the deep learning and the Brain-inspired Intelligence Technology in recent years are discussed. The purpose of this paper is to emphasize a new idea of combining the intelligent algorithms with the classical control methods, and provide some new ideas and practical examples for the intelligent control.

intelligent control  /  biological intelligence  /  automatic control  /  reinforcement learning