Study on Adaptive Strategy of Task and Parameter in Human Simulated Intelligent Control Algorithm

摘要

In order to overcome the puzzle of parameter mismatch in the switching process of human simulated intelligent control, the paper studied on adaptive task and parameter strategy of human simulated intelligent control algorithm. Based on the human-machine learning process, it made the anatomy of causable fault and its produced cause, pointed out the limitation of adaptive function in original algorithm, discussed the adaptive mechanism of error anomaly processing, and presented the improved algorithm of modification control. Taking a two order with time lag process as an example, the experiment of error anomaly processing of adaptive control strategy demonstrated its better complementarity for human simulated intelligent control algorithm. The study result shows that the presented adaptive strategy of error anomaly processing can cover a wider application in the switching process of human simulated intelligent control.