Shiro Masuda

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Fictitious reference iterative tuning (FRIT) is a direct control parameter tuning method using one-shot experimental input-output data with no need for help from a plant model. FRIT searches control parameters so that the plant output follows the reference model output, which specifies an ideal response for the reference signal. However, if an inappropriate(More)
  • Shiro Masuda
  • 2011 IEEE International Conference on Control…
  • 2011
The disturbance attenuation FRIT method for regulator problems tunes the control parameters so that the disturbance response follows the disturbance reference model output. We have recently proposed such a disturbance attenuation FRIT method using input-output data generated by disturbances. This paper applies the disturbance attenuation FRIT method to a(More)
Abstract. This paper proposes an approach to monitoring and scheduling methods for repetitive MIMO-FIFO DESs. We use max-plus algebra for modeling and formulation, known as an effective approach for controller design for this type of system. Because a certain type of linear equations in max-plus algebra can represent the system’s behavior, the principal(More)
In this paper, an improved hybrid optimization model based on grey GM (1,1) model is proposed to develop the prediction model in power systems. To realize more accurate prediction, the regression model is firstly integrated into GM (1,1) through compensation for the residual error series. The improved model is defined as RGM (1,1). Furthermore, Markov chain(More)
A direct design approaches based on input-output measurements with no need for help from a plant model have attracted attention from several researchers. We have recently proposed such a disturbance attenuation FRIT method using input-output data generated by disturbances. The approach has advantages that it can tune PID gains to improve feedback(More)
The direct control parameter tuning methods derive the control parameters from the one-shot experimental input and output data with no need of help from the plant model. Most prior methods have been based on the perfect model matching design strategy so that the output of the closed loop system should follow the prescribed reference model output. In(More)
Reliability prediction has been widely studied in many research fields to improve product and system reliability in manufacturing systems. Traditionally, to establish the prediction model, modelers would use all training data without preference. However, the prediction model based only on the most recent data may have better performance. In this paper, to(More)