Optimization method for multi-motor cooperative control PID parameters based on clone immune algorithm and particle swarm algorithm

Abstract

The invention claims an optimization method for multi-motor cooperative control PID parameters based on a clone immune algorithm and a particle swarm algorithm, and relates to the improvement of the particle swarm algorithm using the clone immune algorithm. PID control is the control method most widely used in process control, and the key is the optimization of PID parameters. In the invention, the particle swarm algorithm is first optimized by using a clonal selection algorithm. A clone immune operation is added based on the particle swarm algorithm. The particles in an external optimal solution set are subjected to clone replication, clone mutation and clone selection operations when the particle swarm algorithm falls into the local optimal solution, thereby improving the diversity of particles, helping the algorithm to jump out of a local optimal solution, avoiding premature convergence, and improving the accuracy of the solution. Compared with the particle swarm algorithm alone, the method can effectively solve the local optimal phenomenon that occurs when the particle swarm algorithm turns PID control parameters.

Description

technical field [0001] The invention belongs to the field of multi-motor cooperative control, and specifically belongs to the optimization of multi-motor cooperative control PID parameters by using a modified particle swarm algorithm. Background technique [0002] With the development of industrial automation, multi-motor cooperative control is widely used, such as printing equipment, paper machines, precision machining machine tools, etc. In these manufacturing and production process automation control systems, the quality of coordinated motion performance among multiple motors directly affects the reliability and control accuracy of the system. [0003] In 1980, Koren proposed a cross-coupling cooperative control method, using the actual output difference between the motors to compensate the two motors, thereby improving the synchronization between the motors. This cooperative control method is a coupling control method specially for dual motor systems. Compared with the ...

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Problems solved by technology

[0014] When using the particle swarm optimization algorithm to optimize the PID parameters of multi-motor cooperative control, the algorithm will fall into a local optimal state during the optimization process, making the result not the global optimal solution. Therefore, the particle swarm algorithm optimization of PID parameters also has certain defects and needs to be improved.

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