Feedback adaptive rate parameters optimization of full-order state observer

It is difficult to find the optimal solution in existing design of feedback adaptive rate PI parameters of full-order state observer, a feedback adaptive rate PI parameter optimization algorithm of full-order state observer based on improved particle swarm optimization algorithm was proposed. Firstly, according to frequency domain design method, design criterion of the feedback adaptive rate parameters and the main factors affecting parameter design were given. Then several sets of parameter values designed and encoded by the design criterion were mixed into the random initial population to increase the number of fine individuals in the initial population, so as to improve convergence speed and search efficiency. Finally, the optimal value of PI parameters was obtained by coding, initializing population and parameter setting, fitness evaluating and updating particle velocity and location. The experimental results show that the speed estimation accuracy of PI parameters obtained by the optimization algorithm is obviously better than that of the traditional trial method when the slope is given 0.2 pu and 0.6 pu rotational speed, regardless of no-load startup or load operation，and the accuracy can meet requirements of technical indexes of mine-used hoist.