PID parameter optimization method based on adaptive fruit fly optimization algorithm

Abstract

A PID parameter optimization method based on the adaptive fruit fly optimization algorithm, which introduces the basic fruit fly optimization algorithm (FOA) into the adaptive search range of the radius adjustment coefficient, and introduces the odor search fitness function of penalty control into the adaptive fruit fly optimization algorithm As an evaluation standard, finding the optimal PID parameter value specifically includes the following steps: 1) Selection of fitness function, 2) Algorithm design of PID controller; 3) Algorithm execution process to optimize PID parameters; 4) Output optimal fitness Function values ​​and PID control parameters; the invention provides a PID parameter optimization method based on an adaptive fruit fly optimization algorithm with high algorithm control precision, fast response speed and good robustness.

Description

Technical field [0001] The invention relates to the technical field of PID parameter optimization methods, in particular to a PID parameter optimization method based on an adaptive fruit fly optimization algorithm. Background technique [0002] PID controller is widely used in industrial process control because of its simple algorithm, good robustness and high reliability. The parameter tuning of the traditional PID controller requires the summary of human experience, and it is difficult to obtain the ideal optimal value. Genetic algorithm programming is more complicated and has many parameters; particle swarm algorithm weakens in the later stage of evolution and is easy to fall into local optimum. At the same time, the basic fruit fly algorithm does not consider the adaptive change of the optimization step length, which makes the optimization accuracy of the algorithm low, the convergence speed is slow, and the number of iterations and time are increased. Summary of the invent...

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