An AdaptiveSelf Tuning Regulator with Genetic Controller Tuning

This paper presents the development of a Genetic Algorithm Supervisory Loop (GASL) to enhance the performance of Adaptive Controllers in the Self Tuning Regulator (STR) framework. The GASL is designed to tune the identification model and control parameters to achieve an optimum performance of the process. The STR controller used to demonstrate the technique effectiveness is a real time Proportional plus Integral plus Derivative (PID) algorithm. The addition of the GASL to the PID STR provides superior performance by expanding the STR’s ability to maintain control of nonlinear systems under large and quick shifts in system modes and/or disturbances. In test cases, the basic STR shows performance deterioration, while the GAS enhanced STR maintained desirable performances. The GASL developed is applied to a nonlinear adaptive suspension system for investigation and assessment. Investigations results show the effectiveness of utilizing the GASL within the adaptive STR framework.