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Thirasit Kusolsongtawee, Soorathep Kheawhom, Sorin Olaru, Pornchai Bumroongsri
Pág. 25 - 37
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Siwaporn Duangsri, Soorathep Kheawhom, Pornchai Bumroongsri
Pág. 157 - 169
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Pornchai Bumroongsri, Soorathep Kheawhom
Pág. 97 - 106
In this paper, we consider an application of robust model predictive control to optimal dosing of breast cancer chemotherapy. The model-patient mismatch is handled by computing an ellipsoidal invariant set containing the measured patient's states at each...
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Pornchai Bumroongsri, Soorathep Kheawhom
Pág. 87 - 104
In this paper, interpolation-based off-line robust MPC for uncertain polytopic discrete-time systems is presented. Instead of solving an on-line optimization problem at each sampling time to find a state feedback gain, a sequence of state feedback gains ...
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Pornchai Bumroongsri, Soorathep Kheawhom
Pág. 73 - 90
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Pornchai Bumroongsri, Soorathep Kheawhom
Pág. 61 - 72
In this paper, the model predictive control (MPC) algorithm for linear parameter varying (LPV) systems is proposed. The proposed algorithm consists of two steps. The first step is derived by using parameter-dependent Lyapunov function and the second step...
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Pornchai Bumroongsri, Soorathep Kheawhom
Pág. 73 - 90
In this paper, an off-line synthesis approach to robust constrained model predictive control for uncertain polytopic discrete-time systems is presented. Most of the computational burdens are moved off-line by pre-computing a sequence of state feedback co...
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Siwaporn Duangsri, Soorathep Kheawhom, Pornchai Bumroongsri
Pág. 157 - 169
Data reconciliation is a mathematical approach that improves the quality of measurements by calculating the reconciled data that satisfies the process constraints. The conventional data reconciliation approach relies on the process model that contains th...
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