A Survey of Identification Experimental System Parameters Using Genetic Algorithm

System parameter identification is the process of finding system parameters to convert physical control signals (usually torque) from theoretical controllers into signals that the hardware can generate for communication connected to model’s executive structure. Simple SIMO systems, like balanced vehicles, often employ PID controllers due to their straightforward design and effectiveness. The algorithm’s simplicity is extensively elucidated in document [1]. Linear controllers and their parameters are typically determined through experimentation and expert knowledge. However, for advanced controllers such as LQR, H Infinity, and SMC, a trial-and-error approach is not viable due to their complexity and the need for precise tuning.