A PSO identification algorithm for temperature adaptive adjustment system

In the field of reliability and environmental testing, temperature system is essential for simulating temperature conditions. The temperature system is a time-varying, large time-delay and nonlinear system. When the system parameters are changed, the target value can not reach the set-target value. The closed-loop identification is always one of the main contents in the field of industrial advanced control, the Particle Swarm Optimization algorithm is an effective clustering algorithm for solving optimization problems. In this paper, the Particle Swarm Optimization algorithm is firstly applied to the parameter identification of the temperature system model in the test chamber controller in the field of reliability and environmental testing, and the accuracy of the simulation can meet the engineering requirements.