Multivariable process distillation column model prediction control optimization PID control method

Abstract

The invention discloses a multivariable process distillation column model prediction control optimization PID control method. According to the invention, an extended non-minimum state space model predictive control method and a conventional PID control algorithm are combined. The method comprises the steps of: firstly establishing a multivariable process distillation column state space model, and excavating basic process characteristics; then and combined with a state process and an output error of the multivariable process in a distillation column, establishing an extended non-minimum state space model. Based on the models and an optimization idea, the model predictive control method is utilized for setting parameters of a PID controller, and finally PID control over the multivariable process in the distillation column is realized, so that the controlling performance of the multivariable system is effectively improved, the system overshoot is obviously reduced, the controlling performance is improved, the control structure is ensured to be simple, the defects of conventional PID control are overcome, and the good controlling performance is ensured.

Description

technical field [0001] The invention belongs to the technical field of automation and relates to a distillation tower model predictive control optimization PID control method for a multivariable process. Background technique [0002] In the actual industrial process, due to the simple structure and convenient operation of PID control, it has been widely used in the actual process control system. However, with the development of industry, people have higher and higher requirements for product quality, energy consumption and environmental protection, and stricter requirements for the control accuracy of industrial processes. The traditional PID control method is difficult to further improve the control level, and the control process changes. more complicated. For the multi-variable object of the distillation column, the parameter setting process of the traditional PID control is relatively complicated, and may often fail to meet the required control performance indicators and...

AI Technical Summary

Problems solved by technology

However, with the development of industry, people have higher and higher requirements on product quality, energy consumption and environmental protection, and stricter requirements on the control accuracy of industrial processes. The traditional PID control method is difficult to further improve the control level, and the control process changes more complicated

For the multi-variable object of the distillation column, the parameter setting process of the traditional PID control is relatively complicated, and may often fail to meet the required control performance indicators and control accuracy

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