Hiroki Shibasaki

Controller design approach based on linear programming.

This study explains and demonstrates the design method for a control system with a load disturbance observer. Observer gains are determined by linear programming (LP) in terms of the Routh-Hurwitz stability criterion and the final-value theorem. In addition, the control model has a feedback structure, and feedback gains are determined to be the linear quadratic regulator. The simulation results confirmed that compared with the conventional method, the output estimated by our proposed method converges to a reference input faster when a load disturbance is added to a control system. In addition, we also confirmed the effectiveness of the proposed method by performing an experiment with a DC motor.

A design of a robust discrete-time controller.

In this paper, we proposed a robust discrete-time controller. This control system, which is derived from the idea of the normalized plant, does not include plant parameters. Thus, we obtain a control system independent of plant parameters and that has the same structure as a conventional optimal servo control system. Simulation and experimental results show that the proposed method is fairly robust to plant parameter variations and external disturbances.

High speed activation and stopping control system using the bang-bang control for a DC motor

In this paper, we propose a high speed activation and stopping control system using the bang-bang control for a dc motor. The Bang-Bang control is able to control the actuator in high speed activation and stopping. However, when there are torque disturbances in actuators, the target-position is not able to be precisely stopped. Therefore, we design the switching control system. It operates from the bang-bang control to PID control continuously. Here, the system includes various factors to consider designing. For example, calculating switching time of bang-bang input, and how to operate continuously from the bang-bang control to PID control, and so on. Theoretical analysis is described and how to design the proposed method in detail. In simulation studies, it shows results of various cases to indicate the effectiveness of our proposed method.

Discrete modified Smith predictor based on optimal control method for a plant with an integrator

In this paper, a discrete modified Smith predictor based on optimal control design method is proposed. A plant with long dead-time is controlled by means of a predicted-state feedback technique and a modified Smith predictor composed of a plant predictor and an observer. In this method, states of a plant are obtained by an observer because the states are not measured directly in practice. The advantages of the proposed method are that a steady-state error caused by a disturbance can be eliminated and that an unstable plant can be made stable unlike conventional methods such as Smith predictor and Internal Model Control. It also achieves good robustness to modeling errors by adjusting weights of LQI-scheme. In simulation studies, it is shown that the proposed method is effective for these plants. Furthermore, by applying the proposed method to a pneumatic actuator, the effectiveness of the method is confirmed.

Simple model following control design methods for a stable and an unstable plant

In this paper, we propose simple model following control design methods for a stable and an unstable plant. Each method is based on the pole placement using model parameters. In simulation studies, we show various cases including a nominal plant and the plant with a modeling error for a stable plant, an unstable plant, and a DC motor. These results show that the proposed methods have been superior performances.

A model-following positioning control system based on modified sliding mode control

This study presents a model-following positioning control system based on modified sliding mode control. In the proposed method, a robust gain matrix prevents the dependence on the plant parameters by applying the switching function to an error dynamics equation. Simulation studies are applied to a nominal plant with stable and unstable terms, and a plant with a modeling error and an input-side disturbance. Simulation and experimental results indicate the effectiveness of this method in determining a robust gain matrix. The proposed method further demonstrates positioning control with superior performance.

A model-following control using a robust gain matrix based on the normalized plant

This study describes and demonstrates the model-following control using a robust gain matrix based on the normalized plant. The normalized plant is constructed by inserting the matrices for normalizing into the original plant, rendering it independent of the plant parameters. The robust gain matrix also adopts a switching function determined by the linear quadratic regulator (LQR) method. The robust gain matrix is then incorporated into a model-following control and evaluated in simulations of the nominal plant, the plant with a modeling error, and the plant with disturbances. The superior performance of the proposed method is demonstrated in loaded and unloaded DC motor experiments.

An approach to model-following controller design based on a stabilized digital inverse system

This article explains our approach to designing a model-following controller based on a stabilized digital inverse system. We use an inter-sample auxiliary observation output from the model as an input to the inverse system. We then design the inverse system for minimum and non-minimum phase plants. In order to reposition the unstable poles of the inverse system on a stable region, we determine the optimal gain vector using a linear quadratic regulator. We confirm the effectiveness of our proposed method by performing simulations for several plants and conducting an experiment with a direct current motor.

Modified Model-Following Sliding Mode Control Based on the Active Disturbance Rejection Control

In this paper, modified model - following sliding mode control based on the active disturbance rejection control observer is proposed and demonstrated. We introduce the Active disturbance rejection control with disturbance observer. the Improved ADRC is normalizing the plant and the removal characteristics of the input-side disturbance. Therefore, the plant is changed to the characteristics not having the plant parameters. The controller is used the sliding mode control. In the sliding mode control, the reachability condition is improved the adaptive control by using the improved ADRC. The simulation studies are applied to a plant with stable, unstable terms, and a stable plant with an integrator. Simulation results show that this method can get the superior performance of positioning control.

An H ∞ controller design based on the butterworth filter conversion

This paper describes and shows an H∞ controller design based on the Butterworth filter conversion. The proposed method refers to the conception of a normalized plant. By converting the control target to a Butterworth filter, it is not necessary to redesign the controller depending on the control target. Simulation and experimental results show the proposed method to be robust against an external disturbance and a modeling error.