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检索条件"主题词=Nonlinear Model Predictive Control"

共 1663 条记录，以下是1581-1590 订阅

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model predictive control of a Dual Output Seven-Level Rectifier

Model Predictive Control of a Dual Output Seven-Level Rectif...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Mohammad Sleiman Handy Fortin Blanchette Luc-Andre Gregoire Hadi Kanaan Kamal Al-Haddad Ecole de Technologie Suprieure Saint-Joseph University Faculty of Engineering ESIB CTS

ISBN: (纸本)9781479917631

In this paper, a component efficient multilevel rectifier is modeled and controlled using model predictive control (MPC) technique. The recently introduced Capacitor Tied Switches (CTS) converter structure features two distinct dc-load terminals which can operate at different voltage levels while experiencing high voltage levels at the ac-side terminals. The CTS converter structure inherits attractive features from the efficiency and power quality perspectives, with excellent topology performance which was validated through different simulation scenarios.

关键词： Multilevel rectifier model predictive control (MPC) Asymmetric converter Packed U-Cell (PUC) Active PFC rectifier Buck-boost rectifier Capacitor Tied Switches (CTS) voltage level model predictive control predictive control Rectifiers distributed model predictive control nonlinear model predictive control CTS loading station Converters

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Robustness of steady-state optimality in economic model predictive control

Robustness of steady-state optimality in economic model pred...

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IEEE Annual Conference on Decision and control

作者： Matthias A. Muller Frank Allgower Institute for Systems Theory and Automatic Control University of Stuttgart

ISBN: (纸本)9781467320658

We study a dissipativity property which was recently used in several results on economic model predictive control to ensure optimal operation of a system at steady-state as well as stability. This dissipativity property involves a supply rate which depends on the state and input constraints imposed on the system. The main contribution of this paper is to show that under certain conditions, this dissipativity property, and hence also optimal operation of a system at steady-state, is robust with respect to small changes in the constraint set. Moreover, we show that further results are possible if a certain convexity assumption is satisfied.

关键词： Economic models predictive control Optimal operation Steady state distributed model predictive control nonlinear model predictive control Robustness optimality optical coherence tomography angiography device system parameter

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Weight recentered barrier functions and smooth polytopic terminal set formulations for linear model predictive control

Weight recentered barrier functions and smooth polytopic ter...

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American control Conference

作者： Christian Feller Christian Ebenbauer Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 70550 Stuttgart

ISBN: (纸本)9781479917730

In the context of barrier function based model predictive control, a suitable recentering of the underlying barrier functions is essential for ensuring stability properties of the closed-loop system. We present a novel method for the recentering of logarithmic barrier functions which can be applied to a wide class of problems. In contrast to existing approaches, the recentering is achieved by a suitable weighting of the respective barrier functions and does not involve any gradient terms. In addition, a new approach towards the design of stabilizing barrier function based linear MPC formulations with polytopic terminal sets is presented which demonstrates possible benefits of the new recentering procedure.

关键词： barrier function predictive control nonlinear model predictive control linear models Closed loop systems

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Trajectory Tracking control for Autonomous Vehicles in Different Cut-in Scenarios

Trajectory Tracking Control for Autonomous Vehicles in Diffe...

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American control Conference

作者： Yimin Chen Junmin Wang University of Texas at Austin Austin Texas 78712 USA

ISBN: (纸本)9781538679012;9781538679265

Trajectory tracking in the cut-in scenarios is challenging because the autonomous vehicles have to follow the reference trajectory and cooperate with the cut-in vehicles simultaneously. This paper proposes a trajectory tracking control method considering the cut-in vehicles with different behaviors. A model predictive control (MPC) approach incorporating driver behavior prediction is developed to track the reference trajectory and keep a safe distance with the cut-in vehicle. Moreover, the transient process of the cut-in scenario is considered for different cut-in behaviors. By synthesizing the driver behavior prediction with the trajectory tracking control, the relative distance between the autonomous vehicle and the cut-in vehicle gradually reaches the safe distance in the transient process. The designed controller is validated by CarSim simulation. The simulation results show that the controller can not only track the reference trajectory, but also achieve a smooth transient process in different cut-in scenarios.

关键词： Autonomous vehicle trajectory tracking control driver behavior cut-in scenarios model predictive control Autonomous Vehicles Driver Behavior trajectory tracking safety distance tracking control predictive control transient processes vehicle model predictive control nonlinear model predictive control

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Feasible Cooperation Based model predictive control for Freeway Traffic Systems

Feasible Cooperation Based Model Predictive Control for Free...

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IEEE Conference on Decision and control

作者： J.R.D. Frejo E.F. Camacho Dept. de Ingenieria de Sistemas y Automatica Escuela Superior de Ingenieros University of Seville Spain

ISBN: (纸本)9781612848006

This paper proposes a distributed algorithm (Feasible Cooperation based model predictive control, FC-MPC) for the control of freeway traffic systems. FC-MPC will be tested and compared with global, local and communicative MPC techniques in a traffic network of 18 segments with ITS (Intelligent Transport Systems) control signals: ramp meters and variable speed limits. It will be shown that local techniques have a suboptimal behavior and that centralized techniques are very difficult, if not impossible, to implement in real time. Communicative MPC improves the behavior of the controlled system versus the decentralized one. However, the solution is still suboptimal with respect to the centralized performance. On the other hand, FC-MPC is closed to the centralized behavior and has a much lower computational effort that the centralized one.

关键词： traffic network traffic systems model predictive control Freeway predictive control nonlinear model predictive control Variable speed control systems

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Mitigating Power Fluctuations in Electrical Ship Propulsion Using model predictive control with Hybrid Energy Storage System

Mitigating Power Fluctuations in Electrical Ship Propulsion ...

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American control Conference

作者： Jun Hou Jing Sun Heath Hofmann Department of Naval Architecture and Marine Engineering and the Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor Michigan 48109 USA

ISBN: (纸本)9781479932757

Shipboard electric propulsion systems experience large power and torque fluctuations on their drive shaft due to propeller rotational motions and waves. This paper explores new solutions to address the fluctuations by integrating a hybrid energy storage system (HESS) and exploring coordinated power management. A propeller and ship dynamic model, which captures the underlying physical behavior, is established to support the control development and system optimization. Given the fact that both high and low frequency contents exist in the power fluctuations, a combination of battery pack and ultracapacitor bank is proposed, coordinated control is developed, and performance is evaluated in different sea conditions. Simulation results show that the proposed HESS with model predictive control provides substantial benefits in terms of reducing fluctuation and sustaining self-operation, compared to other solutions that involve batteries or ultracapacitors alone. Moreover, our analysis shows that the benefits of HESS are achievable only through both effective power management and device coordination.

关键词： marine propulsion power fluctuation hybrid energy storage development control model predictive control predictive control torque fluctuations battery energy storage system THERMAL ENERGY STORAGE SYSTEMS flywheel energy storage system Supercapacitors nonlinear model predictive control fluctuations Battery Pack HIGH POWER

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Choice of the control horizon in an NMPC strategy for the full-state control of nonholonomic systems

Choice of the control horizon in an NMPC strategy for the fu...

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American control Conference

作者： Matthieu Fruchard Guillaume Allibert Estelle Courtial Laboratoire PRISME Universite d'Orleans France Laboratoire I3S UNS-CNRS Sophia Antipolis France

ISBN: (纸本)9781457710957

This paper addresses the choice of the control horizon in a nonlinear model predictive control (NMPC) strategy for nonholonomic vehicles. The latter can be modeled by chained systems. We establish a relation between the degree of nonholonomy and the minimum length of the control horizon so as to make the full-state control possible. A necessary condition on the control horizon of NMPC is given and theoretically proved whatever the dimension of the chained system considered. The theoretical results are illustrated through simulations on a (2,5) chained system, describing a car-like vehicle with one trailer. Difficult motion objectives that require a lateral displacement are considered, as well as robustness to modeling errors.

关键词： control horizon nonlinear model predictive control

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Regulation Service for the Short-Term Management of Renewable Energy Microgrids with Hybrid Storage using model predictive control

Regulation Service for the Short-Term Management of Renewabl...

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Annual Conference of the IEEE Industrial Electronics Society

作者： F. Garcia C. Bordons Departamento de Ingenieria de Sistemas y Automatica Escuela Superior de Ingenieros. Universidad de Sevilla

ISBN: (纸本)9781479902255

The electricity market rules determine the energy price in the day-ahead market, matching offers from generators to bids from consumers to develop a classic supply and demand equilibrium price, usually on an hourly interval. The unpredictability of renewable energy joined to the penalty deviations used in the regulation market make it difficult for clean energy to play an important role in the system. The use of Energy Storage Systems (ESS) integrated in a microgrid (μG) structure with renewable energy systems using two level scheduling, long-term (40 hours) and short-term (1 hour) appears as a solution to minimize the penalty deviations. In this paper, the short-term regulation service optimization linked to the long-term economical dispatch of a grid-connected renewable energy μG is addressed. The μG includes hybrid energy storage composed of hydrogen storage (HESS), battery storage (BESS) and ultracapacitor storage (UESS). It is managed with model predictive control (MPC) in order to maximize the economical benefit minimizing the degradation causes of each storage system. In order to capture both continuous/discrete dynamics and switching between different operating conditions, the plant is modeled with the framework of mixed logic dynamic (MLD). Taking into account the presence of integer variables, the MPC problem is solved using MIQP (Mixed Integer Quadratic Programming).

关键词： Hybrid systems Interfacing and control of energy storage technology Distributed and Micro- and off-grid generation Hydrogen hybrid systems Renewable energy Cache Memory System Hydrogen model predictive control predictive control Energy costs quadratic programming Clean energy ENERGY SYSTEMS distributed model predictive control nonlinear model predictive control Standing Orders Regulation (biology) Maximum Allowable Concentration

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Lifted implicit integrators for direct optimal control

Lifted implicit integrators for direct optimal control

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IEEE Annual Conference on Decision and control

作者： Rien Quirynen Sebastien Gros Moritz Diehl Department ESAT-STADIUS KU Leuven University Kasteelpark Arenberg 10 3001 Leuven Belgium Department of Signals and Systems Chalmers University of Technology Horsalsvagen 11 SE-412 96 Goteborg Sweden

ISBN: (纸本)9781479978878

nonlinear model predictive control (NMPC) relies on solving an Optimal control Problem (OCP) online at every sampling time. The discretization of the continuous time dynamics requires the deployment of some numerical integration method. To that end, implicit integrators are often preferred when stiff or implicitly defined dynamics are present in the system. Implicit integration schemes, however, are typically more expensive to implement than explicit methods. This paper presents a novel lifting method for implicit integrators which improves their computational efficiency and accuracy in the context of Newton-type optimization algorithms. Similar to the standard lifted Newton, the proposed lifting method requires a marginal implementation effort. This novel approach has been implemented in the ACADO code generation software, and its efficiency illustrated using a nontrivial control example. An improved convergence and a computational speedup of about factor 2 are reported.

关键词： lift integrators Implicit Optimization algorithms Integration Methods Optimal control nonlinear model predictive control Computational efficiency deployment lifts

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Combined probabilistic and set-based uncertainties for a stochastic model predictive control of island energy systems

Combined probabilistic and set-based uncertainties for a sto...

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American control Conference

作者： Julia Sachs Andreas Gienger Oliver Sawodny Institute for System Dynamics University of Stuttgart Postbox 80 11 40 70550 Germany

ISBN: (纸本)9781467386838

Microgrids comprising of diesel generators, storage devices and renewable sources present an effective approach for an economic energy supply to rural areas. This paper presents the development of a stochastic model predictive control (SMPC) with the analytical calculation of chance constraints for the combination of set-based and probabilistic uncertain data. The stochastic uncertainties resulting from changes in load demand and fluctuating power from renewables are directly included in the stochastic optimization problem. To account for these disturbances the presented approach assumes probabilistic constraints on the battery state of charge which can be analytically calculated based on the continuous probability distribution of the uncertainties. The additional set-based uncertainties on the load demand and PV power forecast imply further limitations on the probabilistic constraints. The performance of the SMPC is enhanced by evaluating the probability distribution and probabilistic constraints over several time steps as well as using a relaxation technique to assure feasibility. The presented SMPC approach is used for an efficient optimization of the microgrid operation while reducing the complexity of the operational problem compared to other approaches and satisfying all operation constraints. Simulation studies using a real-world application have been performed to showcase the performance of the proposed method.

关键词： Uncertainty Optimization Probabilistic logic Generators Stochastic processes Batteries Mathematical model Probabilistic logic Markov chain Batteries dynamos SMPC Uncertainty Battery charging status Mathematical model Relaxation Techniques distributed model predictive control nonlinear model predictive control predictive control Stochastic Processes Stochastic models Probability distribution

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