A Study on Disturbance Suppression of Self-Tuning Generalized Predictive Control Method with Reduced Computational Complexity

Generalized Predictive Control (GPC) is one of the model-based control methods. The control law is derived by a performance index consisting of the error between the reference signal and the output prediction, and the sum of squares of the control inputs. In recent research, we proposed a new output...

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Bibliographic Details
Main Author: Yanou, Akira
Format: Conference Proceeding
Language:English
Subjects:
Computational complexity
Design methodology
Disturbance response characteristics
Generalized predictive control
Manufacturing automation
Numerical simulation
Performance analysis
Predictive control
Predictive models
Self-tuning controller
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Summary:Generalized Predictive Control (GPC) is one of the model-based control methods. The control law is derived by a performance index consisting of the error between the reference signal and the output prediction, and the sum of squares of the control inputs. In recent research, we proposed a new output prediction and extended the control law so that the disturbance response characteristics can be adjusted without changing the output response characteristics. However, there was a problem that the amount of calculation increased when using the self-tuning controller. Therefore, in this paper, we propose a method to reduce the computational complexity while enabling readjustment of the disturbance response characteristics without changing the closed-loop characteristics by adopting a new method to reduce the computational complexity of the control law. The effectiveness of the proposed method is demonstrated by numerical simulations.
ISSN:1946-0759
DOI:10.1109/ETFA54631.2023.10275540