神经网络优化PID的船舶发动机自动控制

Automatic control of marine engine based on neural network optimization PID

船舶发动机自动控制系统十分复杂且有高阶强祸合的非线性特征。传统的船舶发动机采用的PID控制器,在船舶运行的整个制过程中其参数都固定不变,这就导致了船舶在实际运行过程中出现状态变化和系统参数的不确定性问题,难以达到最佳的船舶控制效果。而人工神经网络系统是对人脑功能的基本特性进行抽象简化的模拟系统,具有灵活和精准的特点以及良好的非线性处理和容错性能,在现代工业中得到了广泛应用。利用神经网络优化PID控制系统可有效解决传统船舶发动机运行过程中存在的不确定非线性问题。因此结合神经网络优化PID控制系统对船舶发动机自动控制系统进行研究和设计,并通过仿真实验验证神经网络优化PID的船舶发动机自动控制系统在运行过程中对船舶的控制能力。实验结果证实该系统能有效解决传统发动机中存在的非线性问题,在恶劣条件及故障情况下仍能保障船舶稳定运行。

The automatic control system of marine engine is very complex and has high-order strong-evil nonlinear characteristics. The PID controller used in the traditional ship engine is fixed in the whole process of ship operation, which leads to the problem of state change and system parameter uncertainty in the actual operation process of the ship, and it is difficult to achieve the best ship control effect. The artificial neural network system is an abstract and simplified simulation system for the basic characteristics of human brain function, with flexible and accurate characteristics and good nonlinear processing and fault tolerance, has been widely used in modern industry. Using neural network to optimize PID control system can effectively solve the uncertain nonlinear problems existing in the traditional ship engine operation process. Therefore,combined with neural network optimization PID control system to study and design the ship engine automatic control system, and through the simulation experiment to verify the neural network optimization PID of the ship engine automatic control system in the process of operation of the ship 's control ability. The experimental results show that the system can effectively solve the nonlinear problems existing in the traditional engine, and can still guarantee the stable operation of the ship under severe conditions and fault conditions.