|Budget Amount *help
¥1,900,000 (Direct Cost: ¥1,900,000)
Fiscal Year 2002: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2001: ¥1,000,000 (Direct Cost: ¥1,000,000)
We investigated methods of updating the model adaptively based on online data in the control loop: a combination of an extension of LPV systems modeling and an extension of model predictive control scheme. On the basis of these discussions, we formulated control problems, and proposed solutions and algorithms for calculating the controls. In particular, we paid attention to the role of the information delay and the obstacles raised by the information delays.
First, as controlled objectives, we focused electro-hydraulic servosystems, which contain nonlinear elements and uncertainties and are difficult to be modeled exactly. We constructed a linear local model in the neighborhood of each selected operating point of the electro-hydraulic system, and built an LPV global model by using load variations as a scheduling parameter. For the LPV systems, we derived the worst-case optimal control strategy, and demonstrated the effectiveness of the control strategy in the computer simulations and in the real plants. Second, as a typical difficulty in controlling the plant based on the local models, we focused the problem caused by information delays in the state, input and output. In particular, we investigate how to conquer the input and output delays in controlling the plant. The worst-case optimal control scheme was proposed; the finite-dimensional algorithm for constructing the control scheme was derived, the predictor-observer structure of the control scheme was clarified, and the illustrative numerical simulations were reported.