Research on the Control System of Greenhouse Based on Particle Swarm and Neural Network

In terms of problems from the quantification factor and scaling factor for fuzzy controller in networked control systems (NCS), which are hard to tackle with conventional empirical methods, the improved quantum particle swarm optimization (IQPSO) based on adaptive mutation of the artificial bee colony operator is proposed in this paper, which is inspired by the thought of searching for nectar source in artificial bee colony algorithm (ABC algorithm) and the performance test is conducted against three types of typical test functions. Then IQPSO is applied into the parameter optimization of fuzzy controller in NCS with time delays, and one typical case in the industrial process control is used to perform the simulated experiment, of which the results indicate that fuzzy controller designed with the aid of IQPSO algorithm PID controller is of better control effect and higher adaptive capacity than those of the PID controller designed with IQPSO and the fuzzy controller designed with standard QPSO algorithm.