Controller design approach based on linear programming

“…The modeling error is applied to ap1. Models are given by (22) in the case of the manipulated variable (17) and by (25) in the case of the manipulated variable (19). Here, the weight matrix Q and the weight coefficient R with LQR method for the optimal gain matrix G are as (24).…”

Section: Unstable Plantmentioning

confidence: 99%

“…The model is given by (25) in case of the manipulated variable (9). The modeling error is applied to 120.2, that is, 120.2×10 = 1202.…”

Section: Time [Sec]mentioning

confidence: 99%

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A design method of a model-following control system

Shibasaki

Yusof

Ishida

2015

Int. J. Control Autom. Syst.

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This paper describes and demonstrates a model-following control system that is based on a switching function where an optimal gain matrix is determined by the LQR method. In our proposed method, the optimal gain matrix is derived such that it does not depend on the plant parameters. Simulation results show various cases including the nominal plant and the plant with a modeling error. The experimental study is also performed using a DC motor. The simulation and experimental results show that the proposed method has superior effectiveness.

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“…Fig. 7 is a photograph of the DC motor [12], [14], [16], [18] used in the experimental study, which was made by PID Corporation (PID-QET ii). The motor is equipped with an inertial load disk of radius 0.0248 m and weight 0.068 kg.…”

Section: Experimental Studymentioning

confidence: 99%

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

Shibasaki

Yusof

Ishida

2015

2015 10th Asian Control Conference (ASCC)

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This study describes and demonstrates the modelfollowing 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.

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Controller design approach based on linear programming

Cited by 9 publications

References 24 publications

Design of a Model-following Controller Using a Decoupling Active Disturbance Rejection Control Method

Design of a Model-following Controller Using a Decoupling Active Disturbance Rejection Control Method

A design method of a model-following control system

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

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