The Application And Research Of Evolutionary Algorithms In The Temperature Control Of Aircraft Ground Air Conditioning Carts

Aircraft ground air conditioning carts are one of security equipments when the aircrafts are repaired and maintained on the ground. China has vast territory and variable climate, and the factors determine that the working environment of the aircraft ground of airs conditioning carts is complicated and variable. The temperature control system is the core component of aircraft ground air conditioning carts. At present in the automatic control field, PID control is one of the widely used control strategy, this is because the PID control has the advantages of simple structure, easy implementation, good robustness, etc. However, for the complex systems whose working environments are uncertain such as imprecise, nonlinear or time-varying models, the traditional PID control has the defects of high overshoot, slow response, weak anti-interference ability and so on. Therefore in this paper, the genetic algorithm and the particle swarm algorithm are introduced based on traditional PID. The genetic algorithm and the particle swarm algorithm are used respectively to tunes PID parameters, and the Matlab simulation experiments are carried out. The experimental results show that the PID parameters tuning based on genetic algorithm and the particle swarm optimization algorithm are all better than the traditional PID control in stability, precision, anti-interference ability, etc. However, there is "degenerate" phenomenon based on the genetic algorithm PID parameters tuning, so the stability is poor, and it is easy to fall into local optimum based on the particle swarm optimization, so accuracy is not satisfactory.On the basis of analyzing the advantages and disadvantages of the genetic algorithm and the particle swarm algorithm, this paper proposes the genetic-particle swarm optimization PID control method with good stability, high accuracy, strong anti-interference. It utilizes traditional PID method, combines with their respective advantages of the genetic algorithm and the particle swarm optimization algorithm, and achieves the PID parameters online tuning. It has been proved by the Matlab simulation experimental results that this algorithm has small overshoot, fast response, high precision, strong anti-interference ability, and other advantages. In the meanwhile, it has greatly improved the performance of the PID control, and it is very suitable for the temperature control of the aircraft air conditioning carts.