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Design of Switching State Observer for Irregularly Delayed Measurement |
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Kenji Sugimoto, Kentaro Noto(Nara Institute of Science and Technology, Japan) |
| In networked control systems, sensing may sometimes suffer from irregular delay of measurement signal transmission due to congestion. This phenomenon is called "jitter" and deteriorates the system performance seriously. This paper proposes a new state observer design that functions properly against jitter, based on the time-stamp of the received signal packets. This is achieved by tracing back the estimated state and by switching observer gains, so that the error system remains stable with a common Lyapunov function. A conventional scheme for the same objective adopted a high order state obse |
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A preliminary study on gain-scheduled model predictive control of floating offshore wind turbines |
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Ryo Watanabe, Naoyuki Hara, Keiji Konishi(Osaka Prefecture University, Japan) |
| Floating concept in offshore wind turbines has attracted growing attention recently. In this paper, we propose gain-scheduled model predictive control for floating wind turbines to reduce platform pitch fluctuations and to regulate the generator power. |
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Combined Feedforward/Disturbance Observer-Based Control of Pump-Controlled Electro-Hydrostatic Actuation System |
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Hyung-Tae Seo, Dae-Gyeom Kang, Yun-Pyo Hong, Kyung-Soo Kim(KAIST, Korea), Jae-Kwan Ryu, Junsik Lee(LIG nex1, Korea) |
| This paper studies the high performance robust motion control of a pump-controlled electro-hydrostatic actuation (EHA) with single-rod hydraulic actuator. Started from the observation that EHA system has almost linear dynamics in small operating range, the linear control technique is taken into account. To nominalize the nonlinear system, the disturbance observer is implemented to the existing closed-loop system. Thanks to that, the feedforward control for linearized system provides rapid response. The performance of the proposed method is validated via experiments. |
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Robust performance optimization for structural uncertainties in data-driven regulatory control parameter tuning |
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Riku Yoshino, Shiro Masuda(Tokyo Metropolitan University, Japan) |
| The present work proposes a method for robust performance optimization for structural uncertainties
in data-driven regulatory control parameter tuning. The proposed method formulates a mini-max optimization problem for obtaining the controller realizing robust performance under the assumption that
the range of the variation of plant parameters are known. Since the data-driven approach collects the information of the plant and disturbance model, the derived controller shows better control performance comparing to the model-based case. |
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The model-free PID gain tuning for regulatory control based on generalized minimum variance evaluation with a feedfoward compensator |
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Shotaro Takahashi, Shiro Masuda(Tokyo Metropolitan University, Japan) |
| Recently, we have proposed a model-free PID gain tuning method for regulatory control based on generalized minimum variance evaluation. The present work extends the model-free PID gain tuning method to the case where measurable disturbances are tractrable. The proposed method gives a tuning method for a feedfoward compensator as well as a feedback compensator, such as PID gains. Finally, the effectiveness of the proposed method is shown through numerical simulations. |
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Fuzzy Compensation Technique for Cooperative Control between Two Actuations of an One-wheel Robot |
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Sangdeok Lee, Seul Jung(Chungnam National University, Korea) |
| In this paper, a fuzzy compensation (FC) technique along with the on-line system identification of two actuator systems of a one-wheel robot. Recursive least square (RLS) algorithm is used to identify the system with FIR-typed moving average filters for both a gimbal and a body system. To compensate for uncertainties in the modeling process, a fuzzy compensator is designed. Experimental studies of balancing a one-wheel robot are conducted. Performances by different control schemes, FC without RLS and FC with RLS are compared. |
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