A proposal for robust control performance on cascade control using IMC-based PID control and genetic algorithm
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In most processes, robust control performance is required even if a disturbance occurs to ensure stable performance in the steady-state operation. Cascade control needs to be applied to ensure control performance even during disturbances. However, when cascade control is applied, the design and tuning of the primary controller involves the secondary control loop and the primary process and becomes a form of a higher-order equation. The purpose of this paper is to propose a simple method of the design and tuning for controllers without any complicated structures. In this proposal, the secondary control loop was designed and tuned by the IMC-based PID control considering the cancellations of the poles and zeros between a controller and the process. A genetic algorithm was used to design the best performance in the primary controller. For the performance comparison of the proposal, controllers tuned by the IMCbased PID control and direct synthesis and the fine-tuned controller by the Tyreus–Luyben method were applied in the simulation. Simulations were carried out to confirm the control performance using these controllers. As results of the simulation, this proposal presented better results with nominal models, ±10% parametric uncertainties for the processes, and a disturbance with a twice gain, for both setpoint tracking and disturbance rejection.
Abstract
In most processes, robust control performance is required even if a disturbance occurs to ensure stable performance in the steady-state operation. Cascade control needs to be applied to ensure control performance even during disturbances. However, when cascade control is applied, the design and tuning of the primary controller involves the secondary control loop and the primary process and becomes a form of a higher-order equation. The purpose of this paper is to propose a simple method of the design and tuning for controllers without any complicated structures. In this proposal, the secondary control loop was designed and tuned by the IMC-based PID control considering the cancellations of the poles and zeros between a controller and the process. A genetic algorithm was used to design the best performance in the primary controller. For the performance comparison of the proposal, controllers tuned by the IMCbased PID control and direct synthesis and the fine-tuned controller by the Tyreus–Luyben method were applied in the simulation. Simulations were carried out to confirm the control performance using these controllers. As results of the simulation, this proposal presented better results with nominal models, ±10% parametric uncertainties for the processes, and a disturbance with a twice gain, for both setpoint tracking and disturbance rejection.
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