Study on the improved ACA-based parameters optimization of NLPID controller for flight simulator

A novel NLPID optimization strategy for flight simulator was proposed. In order to enhance the global convergence performance of ACA, the basic ACA was improved by using meeting search strategy and trail decay coefficient self-adaptive adjusting ideology. Furthermore, an improved ACA-based NLPID parameters optimization structure for flight simulator was designed. ITAE performance criteria was adopted in the improved ACA. Finally, the optimized parameters using improved ACA were applied to a high performance flight simulator. The experimental results demonstrate that the NLPID controller has strong robustness against noise. This proposed ACA-based HLPID parameters optimization strategy can also be used to develope other simulation servo system' controllers.