Results 71 to 80 of about 263,923 (197)
Nonlinear Model and Dynamic Behavior of Photovoltaic Grid-Connected Inverter
Applied Sciences, 2020 A photovoltaic grid-connected inverter is a strongly nonlinear system. A model predictive control method can improve control accuracy and dynamic performance.
Zhi-Xian Liao +7 more
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Sparse preconditioning for model predictive control
, 2016 We propose fast O(N) preconditioning, where N is the number of gridpoints on the prediction horizon, for iterative solution of (non)-linear systems appearing in model predictive control methods such as forward-difference Newton-Krylov methods.
Knyazev, Andrew, Malyshev, Alexander
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Preconditioning for continuation model predictive control
, 2015 Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) deals with nonlinear models and/or constraints. A Continuation/GMRES Method for NMPC, suggested by T.
Knyazev, Andrew, Malyshev, Alexander
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Observers in nonlinear model‐based predictive control
International Journal of Robust and Nonlinear Control, 2000 A nonlinear model-based predictive control (NMPC) algorithm for closed-loop systems with separable static nonlinearities is proposed. The key to this development is the concept of invariance which is applied to the error dynamics of an observer in order to develop a NMPC algorithm with guaranteed feasibility and asymptotic stability.
Kouvaritakis, B, Wang, W, Lee, Y
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Mathematics, 2018 This paper addresses the problem of fault-tolerant stabilization of nonlinear processes subject to input constraints, control actuator faults and limited sensor–controller communication.
Da Xue, Nael H. El-Farra
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Closed-Loop Control of Variable Stiffness Actuated Robots via Nonlinear Model Predictive Control
IEEE Access, 2015 Variable stiffness actuation has recently attracted great interest in robotics, especially in areas involving a high degree of human-robot interaction. After investigating various design approaches for variable stiffness actuated (VSA) robots, currently ...
Altay Zhakatayev +2 more
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Nihon Kikai Gakkai ronbunshuModel predictive control is applied to real plants because the control algorithms are easy to understand when designing control systems and can be applied to multivariable systems.
Kazuyoshi KIMURA
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Advances in Mechanical Engineering, 2015 Trajectory tracking and state estimation are significant in the motion planning and intelligent vehicle control. This article focuses on the model predictive control approach for the trajectory tracking of the intelligent vehicles and state estimation of
Hongxiao Yu +4 more
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Differentiable Nonlinear Model Predictive Control
The efficient computation of parametric solution sensitivities is a key challenge in the integration of learning-enhanced methods with nonlinear model predictive control (MPC), as their availability is crucial for many learning algorithms. While approaches presented in the machine learning community are limited to convex or unconstrained formulations ...
Frey, Jonathan +7 more
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Nonlinear model predictive control with polytopic invariant sets
Automatica, 2002 A nonlinear model predictive control (NMPC) method in which low complexity polytopic invariant sets are used in place of ellipsoidal invariant sets is proposed. It is shown that (i) low-complexity polytopic invariant sets have larger volume than invariant ellipsoidal sets; (ii) the systematic design of maximum volume low-complexity invariant polytopes ...
Cannon, M, Deshmukh, V, Kouvaritakis, B
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