Closed-loop iterative particle swarm tuning system and tuning method for thermal multi-loop controller

Abstract

The invention discloses a thermal multi-loop controller closed-loop iterative tuning system and tuning method based on particle swarm calculation. In the invention, the iterative tuning control unit calls the closed-loop identification model unit to identify historical data from the field control system. And input the obtained ARX model order and parameter values ​​into the control loop simulation unit, and then call the closed-loop particle swarm optimization unit to initialize the parameters of the controller to be tuned, and keep the original parameters of the other controllers, and the closed-loop particle swarm optimization unit calls the control loop simulation unit to Each controller to be tuned is closed-loop tuned one by one, and iteratively tuned several times, and the parameters of each controller to be tuned are optimized as the output result of the closed-loop iterative particle swarm tuning system, and the result is output to the field control system. The invention realizes the closed-loop optimal setting of the thermal multi-loop controller parameters, thereby guiding the online adjustment of the controller parameters without affecting the production, and effectively improving the adjustment quality of the control system.

Description

technical field [0001] The invention relates to thermal automatic control technology, in particular to a closed-loop iterative particle swarm tuning system and tuning method for thermal multi-loop controllers. Background technique [0002] PID control is currently the main controller used in thermal control systems. Due to the characteristics of large-scale load changes, long-term continuous operation, nonlinear dynamics, and multiple disturbances in the thermal system, the control performance of the PID controller may deteriorate during operation, resulting in a large oscillation of the adjusted variable, which cannot maintain the safety and economy of the system. run. For this reason, online optimization and setting of PID parameters is required to make the controller adapt to the working conditions again. There are open-loop and closed-loop methods for project tuning of PID controller parameters. The open-loop method requires an open-loop step response experiment, which...

AI Technical Summary

Problems solved by technology

Because the thermal system has multi-variable characteristics, the control loop often includes multiple controllers. When using the conventional method in the closed-loop method to tune the multi-loop control parameters, the controllers are coupled with each other and there are many disturbances, which will cause inconvenience to the tuning; The closed-loop tuning method of intelligent calculation is not easy to converge due to the large number of optimized parameters of multiple controllers, and the optimized parameters are often unreasonable and difficult to apply in practice

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