Suchergebnisse - Parametric predictive control algorithm

A fast, fully distributed nonlinear model predictive control algorithm with parametric sensitivity through Jacobi iteration von Yu, Tianyu, Xu, Zuhua, Zhao, Jun, Chen, Xi, Biegler, Lorenz T.

“… In this work, a fully distributed nonlinear model predictive control (DNMPC) algorithm is developed to accelerate control feedback …”
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Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters von Percival, M.W., Wang, Y., Grosman, B., Dassau, E., Zisser, H., Jovanovič, L., Doyle, F.J.

“… A multi-parametric model predictive control (mpMPC) algorithm for subcutaneous insulin delivery for individuals with type 1 diabetes mellitus (T1DM …”
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A study on the extended horizon adaptive control algorithm of the magnetic support system for high-speed rotor machines von Kurnyta-Mazurek, P., Szolc, T., Henzel, M., Falkowski, K.

“… •Parametric predictive algorithms are suitable for adoption by the AMB control system …”
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An algorithm for robust explicit/multi-parametric model predictive control von Kouramas, K.I., Panos, C., Faísca, N.P., Pistikopoulos, E.N.

“… A new algorithm for robust explicit/multi-parametric Model Predictive Control (MPC) for uncertain, linear discrete-time systems is proposed …”
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Control system with a non-parametric predictive algorithm for a high-speed rotating machine with magnetic bearings von Kurnyta-Mazurek, Paulina, Szolc, Tomasz, Henzel, Maciej, Falkowski, Krzysztof

“… ) algorithm and the proportional-derivative (PD) algorithm are presented. The MAC algorithm is the non-parametric predictive control method that uses an impulse response model …”
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An algorithm for reducing complexity in parametric predictive control von Rossiter, J. A., Kouvaritakis, B., Cannon, M.

“… Multi parametric quadratic programming solutions to predictive control can require large numbers of regions which would make practical implementation difficult …”
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Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming von Kouramas, K.I., Faísca, N.P., Panos, C., Pistikopoulos, E.N.

“… This work presents a new algorithm for solving the explicit/multi-parametric model predictive control (or mp-MPC …”
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Indirect Adaptive MPC for Discrete-Time LTI Systems With Parametric Uncertainties von Dhar, Abhishek, Bhasin, Shubhendu

“… A suitably designed gradient-descent-based indirect adaptive controller, used to handle parametric uncertainties, is combined with a model predictive control (MPC …”
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An Iterative GPC-like nonlinear predictive control algorithm for the parametric Volterra model von Haber, Robert, Bars, Ruth, Arousi, Fakhredin

“… A new iterative nonlinear predictive control algorithm is presented here based on the quadratic parametric Volterra model …”
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Robustness Enhancement Strategy for Flexible Joints Based on Model Predictive Current and Adaptive Control von Yang, Yifei, Zhao, Jianxing, Sun, Xiaodong, Wang, Yong

“… A non-parametric model predictive current control method is employed to update current data in real time …”
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A dynamic programming based approach for explicit model predictive control of hybrid systems von Rivotti, Pedro, Pistikopoulos, Efstratios N.

“… This work presents an algorithm for explicit model predictive control of hybrid systems based on recent developments in constrained dynamic programming and multi-parametric programming …”
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Efficient suboptimal parametric solutions to predictive control for PLC applications von Valencia-Palomo, G., Rossiter, J.A.

“… The prime aim of this paper is to embed a predictive control (MPC) algorithm with constraint handling capabilities into a programmable logic controller (PLC …”
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Towards the integration of process design, control and scheduling: Are we getting closer? von Pistikopoulos, Efstratios N., Diangelakis, Nikolaos A.

“… •Advanced multi-parametric model predictive control schemes.•State-space scheduling representation and multi-parametric optimization solution …”
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Distributed model predictive control for consensus of nonlinear systems via parametric sensitivity von Yu, Tianyu, Zhao, Fei, Xu, Zuhua, Zhao, Jun, Chen, Xi

“… To handle the nonlinear consensus problem, a distributed model predictive control (DMPC …”
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Predictive signature development based on maximizing the area between receiver operating characteristic curves von Huang, Xin, Tian, Lu, Sun, Yan, Chatterjee, Saptarshi, Devanarayan, Viswanath

“… therapeutic and the control groups without assuming any parametric model. We further generalize the proposed algorithm for predictive signature development to maximize the difference of Harrel's C …”
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Multi-parametric Optimization and Control von Pistikopoulos, Efstratios N, Diangelakis, Nikolaos A, Oberdieck, Richard

“… Recent developments in multi-parametric optimization and control Multi-Parametric Optimization and Control provides comprehensive coverage of recent methodological developments for optimal model-based …”
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Explicit/multi-parametric model predictive control of dissipative distributed parameter systems von Liu Liu, Biao Huang, Dubljevic, Stevan

“… This work focuses on the development of an explicit/multi-parametric model predictive control algorithm to stabilize the discrete infinite-dimensional system arising from the discrete state space …”
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Polyhedral feasible set computation of MPC-based optimal control problems von Xie, Lantao, Xie, Lei, Su, Hongye, Wang, Jingdai

“… Feasible sets play an important role in model predictive control &#x0028 MPC &#x0029 optimal control problems &#x0028 OCPs &#x0029 …”
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Deep DeePC: Data‐enabled predictive control with low or no online optimization using deep learning von Zhang, Xuewen, Zhang, Kaixiang, Li, Zhaojian, Yin, Xunyuan

“… Data‐enabled predictive control (DeePC) is a data‐driven control algorithm that utilizes data matrices to form a non …”
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qpOASES: a parametric active-set algorithm for quadratic programming von Ferreau, Hans Joachim, Kirches, Christian, Potschka, Andreas, Bock, Hans Georg, Diehl, Moritz

“… ) problems or require the solution of QP problems on a lower algorithmic level. One relatively recent approach to solve QP problems are parametric active-set methods …”
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