Enhanced PID Control in Internal Combustion Engines and Ship Motion Control

Abstract

 Traditional PID control methods have been widely used in various industries due to their simplicity and effectiveness in regulating system outputs. However, challenges arise when dealing with systems characterized by non-linearity, delays, or external disturbances, necessitating the development of advanced PID control strategies. This paper presents two enhanced PID control approaches tailored for specific applications: intelligent PID control for temperature regulation of internal combustion engines and radial basis function (RBF) neural network-based PID control of marine motion control. The operating principles and algorithms of both approaches are detailed, and by comparing the enhanced methods with traditional PID control algorithms, their superior performance in terms of accuracy and adaptability is demonstrated, and conclusions are drawn regarding the effectiveness and suitability of each approach for their respective applications.