Abstract
Aiming to improve the control ability of smart home, a design scheme of wireless communication control system for intelligent home based on machine learning is proposed. The wireless transmission module, the ZigBee data acquisition module, the AD module, the bus transmission module and the man-machine interface module of the intelligent home control system are constructed. Machine learning algorithm is used to design the control algorithm of intelligent home control system. The robustness of intelligent home control is improved by combining fuzzy PID control scheme. The steady-state error compensation method is adopted to improve the anti-dry-ability of intelligent home control. Combining machine learning algorithm to realize global optimization of intelligent home control. The network module and communication module of the intelligent home control system are constructed under the Zigbee network control protocol, and the hardware design of the intelligent home control system is realized under the integrated DSP environment. The simulation results show that the system has good robustness and stability, and improves the self-adaptability and global stability of smart home control.
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