Simulating Optimal Control of an Inertial Platform Stabilization Loop Using Genetic Algorithms

Abstract

Inertial platform stabilization loop is required with good quickness, high steady precision, strong anti-jamming capability, etc. at the same time, and the traditional PID control is difficult to meet index requirements of the good control performance. Stabilization loop of inertial navigation system platform is treated as a study object, and the mathematical model is built with dynamic loop according to the position of PID controller. Based on the self-adaptive online genetic algorithm tuning, PID control strategy is proposed, and the PID parameters are optimized, and loop model is simulated with MATLAB software. The result of simulation shows that since PID controller is adopted after the genetic algorithm optimization, system control precision, stability and response speed have been improved, enhancing the robustness.