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为满足目前市场对恒温箱系统越来越高的性能要求,设计了一种高性能的恒温箱控制系统。基于PIC16F877A芯片完成系统硬件设计,并采用PID算法作为控制策略。结合混沌的遍历性和粒子群算法的快速趋同效应,设计了一种新型的交替混沌粒子群(ACPSO)优化算法用以整定PID控制器的参数。通过与收缩因子粒子群算法(CPSO)和变惯性权重粒子群算法(IWPSO)比较,证明交替混沌粒子群算法收敛速度快,并能避免粒子群算法容易陷入局部最优的问题。仿真和实际系统测试表明,所设计的控制器可以有效地提高控制系统的性能,应用前景广阔。
In order to meet the increasingly high performance requirements of the incubator system currently on the market, a high-performance incubator control system is designed. Based on PIC16F877A chip to complete the system hardware design and PID algorithm as a control strategy. Combining the ergodicity of chaos and the rapid convergence of particle swarm optimization, a new alternating chaos particle swarm optimization algorithm (ACPSO) is designed to tune the parameters of PID controller. By comparing with contractive factor particle swarm optimization (CPSO) and variable inertia weighted particle swarm optimization (IWPSO), it is proved that alternating chaotic particle swarm optimization algorithm can converge quickly and avoid the particle swarm optimization algorithm being easily trapped in local optimum. The simulation and actual system tests show that the designed controller can effectively improve the performance of the control system and has wide application prospect.