2024 年 144 巻 4 号 p. 380-386
Disturbance suppression is an important issue in control system design. Model Predictive Controllers (MPCs) excel in suppressing known disturbances, offering uniform handling of reference tracking and disturbance response. This study aims to suppress the influence of unknown disturbances using the cost-effective Predictive Functional Control (PFC), a simplified MPC. However, addressing disturbances with PFC necessitates disturbance knowledge or estimation. This paper employs a Disturbance Observer (DOB) for estimation, but a basic DOB struggles with noisy or time-delay systems. To overcome this, our proposed method incorporates a line enhancer from speech processing. Numerical examples in this paper show that the proposed scheme works effectively and achieves the desired disturbance suppression.
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