Results 61 to 70 of about 263,923 (197)
Linear Model Predictive Control of Induction Machine [PDF]
, 2015 This article presents new control algorithm for induction machine based on linear model predictive control (MPC). Controller works in similar manners as field oriented control (FOC), but control is performed in stator coordinates.
Mynář, Z.
core
Nonlinear Model Predictive Control for Constrained Output Path Following
, 2014 We consider the tracking of geometric paths in output spaces of nonlinear systems subject to input and state constraints without pre-specified timing requirements.
Faulwasser, Timm, Findeisen, Rolf
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Aerial navigation in obstructed environments with embedded nonlinear model predictive control
, 2018 We propose a methodology for autonomous aerial navigation and obstacle avoidance of micro aerial vehicles (MAV) using nonlinear model predictive control (NMPC) and we demonstrate its effectiveness with laboratory experiments. The proposed methodology can
andersson +5 more
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IEEE AccessThis paper proposes a novel model predictive control design for Internet of Things (IoT) applications by using the generalized opposition-based learning particle swarm optimization algorithm and cloud computing.
B. Devanathan +2 more
doaj +1 more source
, 2014 In this work, a nonlinear model predictive controller is developed for a batch polymerization process. The physical model of the process is parameterized along a desired trajectory resulting in a trajectory linearized piecewise model (a multiple linear ...
Abbaszadeh, Masoud, Solgi, Reza
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Integration of torque blending and slip control using nonlinear model predictive control [PDF]
, 2016 Antilock Braking System (ABS) is an important active safety feature in preventing accidents during emergency braking. Electrified vehicles which include both hydraulic and regenerative braking systems provide the opportunity to implement brake torque ...
Basrah, M. Sofian +4 more
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Robust tubes in nonlinear model predictive control
IFAC Proceedings Volumes, 2010 Abstract Nonlinear model predictive control (NMPC) strategies based on linearization about predicted system trajectories enable the online NMPC optimization to be performed by a sequence of convex optimization problems. The approach relies on bounds on linearization errors in order to ensure constraint satisfaction and convergence of the performance ...
Cannon, M +3 more
openaire +1 more source
On Stochastic Model Predictive Control with Bounded Control Inputs
, 2009 This paper is concerned with the problem of Model Predictive Control and Rolling Horizon Control of discrete-time systems subject to possibly unbounded random noise inputs, while satisfying hard bounds on the control inputs.
Chatterjee, Debasish +2 more
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Generalized Stabilizing Conditions for Model Predictive Control [PDF]
, 2015 © 2015, The Author(s).This note addresses the tracking problem for model predictive control. It presents simple procedures for both linear and nonlinear constrained model predictive control when the desired equilibrium state is any point in a specified ...
David Mayne, Paola Falugi
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A Sensitivity-Based Approach to Self-Triggered Nonlinear Model Predictive Control
IEEE AccessSelf-triggered control aims to reduce resource utilization, particularly in networked systems, by sampling only when necessary to ensure a specific level of control performance.
Paulina Conrad, Knut Graichen
doaj +1 more source