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

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model predictive control of Remotely Operated Underwater Vehicles

Model Predictive Control of Remotely Operated Underwater Veh...

引用

IEEE Conference on Decision and control

作者： A. Molero R. Dunia J. Cappelletto G. Fernandez Department of Exploration and Production at PDVSA INTEVEP Los Teques Venezuela Department of Chemical Engineering at The University of Texas Austin TX 78712 USA Department of Electronics and Circuits at Universidad Simon Bolivar Caracas Venezuela

ISBN: (纸本)9781612848006

This paper describes the implementation of a model predictive controller novel in an underwater robot vehicle. This work also shows the development of an underwater vehicle model that accounts for physical, hydrodynamic and restorative effects, while the damping coefficients are neglected in the prediction of the vehicle position and orientation. The vehicle kinematic and dynamic models are linearized and arranged into the state space form inside the predictive controller. The model helps to determine the future position and orientation of the vehicle to track a predefined underwater trajectory in an optimal way. The results show that the predictive controller offered significant benefits compared to PID controllers by reducing the MSE and RMS by 40percent and 76percent respectively.

关键词： predictive controllers vehicle underwater vehicles predictive control Automatic vehicle location Vehicle model Damping ratio model predictive control space configuration dynamic models Underwater robots nonlinear model predictive control

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Quadrotor Trajectory Tracking control using Non-Linear model predictive control with ROS Implementation

Quadrotor Trajectory Tracking Control using Non-Linear Model...

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International Conference on control, Mechatronics and Automation (ICCMA)

作者： Mohamed Owis Seif El-Bouhy Ayman El-Badawy Mechatronics Department German University in Cairo Cairo Egypt

ISBN: (纸本)9781728137889

This paper presents a model predictive controller for trajectory tracking control of the quadrotor using the ACADO Toolkit on Matlab/Simulink. model predictive control (MPC) prediction feature and ability to obtain optimal control action yields an accurate trajectory tracking performance. The controller is applied to a quadrotor system. The mathematical model was derived using Newton's and Euler's laws. Simulations for the trajectory tracking test was done for evaluating the trajectory tracking performance. Afterwards, an interface between RotorS Gazebo Simulator and Simulink was implemented using the Robot Operating System (ROS) for validation of the controller's performance. The paper presents the results of both simulations under disturbances to determine the suitability and validity of the proposed control algorithm.

关键词： adaptive control control engineering computing helicopters mobile robots nonlinear control systems optimal control predictive control trajectory control control engineering computing trajectory control predictive control nonlinear control systems Helicopters Mobile robots Optimal control trajectory tracking adaptive control nonlinear model predictive control Computer algorithms control action predictive controllers

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Stochastic Dynamic Optimization and model predictive control based on Polynomial Chaos Theory and Symbolic Arithmetic

Stochastic Dynamic Optimization and Model Predictive Control...

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American control Conference

作者： Matthias von Andrian Richard D. Braatz Massachusetts Institute of Technology Cambridge MA USA

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

Polynomial chaos theory (PCT) quantifies the effects of probabilistic uncertainties on the states and outputs of linear and nonlinear dynamical systems using a model structure that is amenable for use in mathematical formulations for stochastic dynamic optimization and model predictive control. This article presents symbolic methods for automating the construction of exact PCT representations for dynamical systems described by ordinary differential equations (ODEs). The methods automatically construct exact PCT representations for both nonlinear dynamical systems and their linearizations with respect to the state. These methods are implemented using the Matlab Symbolic Toolbox and demonstrated in a case study on the stochastic model predictive control (SMPC) of an automated continuous-flow system for multi-step chemical synthesis. In the case study, SMPC based on a combination of PCT and symbolic algebra has an on-line computational time less than 12 milliseconds per time step, which is more than two orders of magnitude faster than required for real-time implementation.

关键词： Chaos theory nonlinear dynamical systems predictive control model predictive control SMPC nonlinear model predictive control DYNAMICAL SYSTEMS synthesis chemical synthesis symbolic method Polynomial

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Thermal modelling Approach and model predictive control of a Water-cooled PEM Fuel Cell System

Thermal Modelling Approach and Model Predictive Control of a...

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Annual Conference of the IEEE Industrial Electronics Society

作者： J. D. Rojas C. Ocampo-Martinez C. Kunusch Universidad de Costa Rica Inst. de Robotica i Informatica Industrial (CSIC-UPC) Barcelona

ISBN: (纸本)9781479902255

In this paper, a modular thermal modelling approach for a water-cooled Proton Exchange Membrane fuel cell (PEM-FC) stack is proposed. The resultant model is based on the heat flux inside the stack and has been validated in a real test station. Then, a linear model predictive control (MPC) strategy for temperature regulation is designed and tested in simulation with promising results. The proposed MPC controller not only tackles the temperature regulation problem, but also incorporates necessary management constraints for the proper operation of the system in real conditions.

关键词： fuel cell power systems regulation temperature predictive control Proton exchange membrane fuel cells Furnace conveyors normal operation Heat flux model predictive control distributed model predictive control nonlinear model predictive control Maximum Allowable Concentration mucin 1 Pulse code modulation modeling

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model predictive control for Optimal Portfolios with Cointegrated Pairs of Stocks

Model Predictive Control for Optimal Portfolios with Cointeg...

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IEEE Annual Conference on Decision and control

作者： Yuji Yamada James A. Primbs Faculty of Business Sciences University of Tsukuba Department of Systems Engineering University of Texas at Dallas

ISBN: (纸本)9781467320658

In this paper, we demonstrate a model predictive control (MPC) approach to constructing an optimal portfolio consisting of multiple spreads of cointegrated pairs of stocks. It is shown that a conditional mean-variance (MV) optimization problem with any given prediction horizon may be solved efficiently when the spreads of stocks follow a vector autoregressive (VAR) model. Based on the solution to the conditional MV problem, we can apply an MPC strategy that calculates the conditional MV optimal portfolio with a given prediction horizon at each rebalancing period. We also perform out-of-sample simulations using empirical stock price data from Japan, and examine the effects of the length of the prediction horizon, rebalance intervals, and transaction costs.

关键词： Spread portfolio Cointegrated pairs model predictive control Conditional mean-variance optimization Empirical simulations predictive control stocks model predictive control distributed model predictive control nonlinear model predictive control rebalance Horizon Conditional Maximum Allowable Concentration

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model predictive control in Dynamic Economic Dispatch using Weibull Distribution

Model Predictive Control in Dynamic Economic Dispatch using ...

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IEEE Power and Energy Society General Meeting

作者： Chunghun Kim Yonghao Gui Chung Choo Chung Yong-Cheol Kang Dept. of Electrical Engineering Hanyang University Seoul 133-791 KOREA Div. of Electrical and Biomedical Engineering Hanyang University Seoul 133-791 KOREA Dept. of Electrical Engineering and Wind energy Grid- Adaptive Technology (WeGAT) Research Center and Smart Grid Research Center Chonbuk National University KOREA

ISBN: (纸本)9781479913022

This paper develops dynamic economic dispatch (DED) using model predictive control (MPC) based on Weibull probabilistic distribution function (PDF). Firstly we performed economic dispatch (ED) based onWeibull *** considered the probabilistic cost about over-estimated and under-estimated cost of wind power by using Weibull PDF. Secondly we implemented DED formulated in a MPC framework using the maximum wind power capability from the ED results since ED does not consider the ramp rate constraint. By using dispatch error cost, we could consider the current status of reliable generation by using the proposed MPC method. It turns out that the DED using MPC method is very effective in coping with intermittent resource such as wind variability.

关键词： economic dispatch forecasting error ramp rate capability expectation value model predictive control model predictive control Error of prediction predictive control DED AATF Gene Weibull distribution distributed model predictive control nonlinear model predictive control Dispatching Maximum Allowable Concentration EXPECTATION VALUE HEAT RATE emergency room power capability

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Explicit model predictive control on the Air Path of Turbocharged Diesel Engines

Explicit Model Predictive Control on the Air Path of Turboch...

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American control Conference

作者： Dezong Zhao Cunjia Liu Richard Stobart Jiamei Deng Edward Winward Department of Aeronautical and Automotive Engineering Loughborough University Loughborough Leicester UK School of Mechanical and Automotive Engineering Kingston University Kingston upon Thames Surrey UK

ISBN: (纸本)9781479901777

The turbocharged diesel engine is a typical multi-input multi-output (MIMO) system with strong couplings, actuator constraints, and fast dynamics. This paper addresses the air path regulation in turbocharged diesel engines using an explicit model predictive control (EMPC) approach, which allows tracking of the time-varying setpoint values generated by the supervisory level controller while satisfying the actuator constraints. The proposed EMPC framework consists of calibration, engine model identification, controller formulation, and state observer design. The proposed EMPC approach has a low computation requirement and is suitable for implementation in the engine control unit (ECU) on board. The experimental results on a turbocharged Cat C6.6 diesel engine illustrate that the EMPC controller significantly improves the tracking performance of the exhaust emission variables against the decentralized single-input single-output (SISO) control method.

关键词： Explicit model predictive control turbocharged diesel engines exhaust emissions regulation Diesel engines turbocharged diesel engine distributed model predictive control nonlinear model predictive control Turbochargers model predictive control predictive control track time Observers visual tracking Byways Explicit

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model predictive control of Dimethyl Ether Combustion in a Jet Stirred Reactor under Low Temperature Conditions

Model Predictive Control of Dimethyl Ether Combustion in a J...

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American control Conference

作者： Thomas Lammersen Klaus Stoehr Norbert Peters Dirk Abel Institute of Automatic Control RWTH Aachen University 52074 Aachen Germany Institute for Combustion Technology RWTH Aachen University 52074 Aachen Germany

ISBN: (纸本)9781479901777

This paper deals with the control of instabilities and oscillations during the combustion of dimethyl ether (DME) in a continuous jet stirred reactor (JSR). A model predictive control (MPC) is applied to keep the reactor in a steady state at low temperature combustion conditions. The full chemical state of the system consisting of temperature and species concentration is reconstructed from a temperature and a CH concentration signal by an extended Kalman filter. For prediction within the MPC and the filter, a physical model of the JSR including a full combustion reaction mechanism is presented.

关键词： DME JSR MPC JSR dimethyl ether Maximum Allowable Concentration Low temperature Common Cold Combustion Reactors combustion temperature predictive control Extended Kalman filters distributed model predictive control nonlinear model predictive control Agitation

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predictive control of an Autonomous Ground Vehicle using an Iterative Linearization Approach

Predictive Control of an Autonomous Ground Vehicle using an ...

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International IEEE Conference on Intelligent Transportation Systems

作者： Ashwin Carvalho Yiqi Gao Andrew Gray H. Eric Tseng Francesco Borrelli Department of Mechanical Engineering University of California at Berkeley Powertrain Control R&A Ford Motor Company

ISBN: (纸本)9781479929153

This paper presents the design of a controller for an autonomous ground vehicle. The goal is to track the lane centerline while avoiding collisions with obstacles. A nonlinear model predictive control (MPC) framework is used where the control inputs are the front steering angle and the braking torques at the four wheels. The focus of this work is on the development of a tailored algorithm for solving the nonlinear MPC problem. Hardware-in-the-loop simulations with the proposed algorithm show a reduction in the computational time as compared to general purpose nonlinear solvers. Experimental tests on a passenger vehicle at high speeds on low friction road surfaces show the effectiveness of the proposed algorithm.

关键词： predictive control Ground vehicles Passenger cars turning angle control input nonlinear model predictive control computational time Maximum Allowable Concentration Linearization braking torque controller design

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Cooperative distributed model predictive control for linear plants subject to convex economic objectives

Cooperative distributed model predictive control for linear ...

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IEEE Conference on Decision and control

作者： Jaehwa Lee David Angeli Infineon Villach Austria

ISBN: (纸本)9781612848006

In this paper we propose a cooperative distributed economic model predictive control strategy for linear systems which consist of finite number of subsystems. The suggested control strategy is generating control feedback which converges to the centralized optimal solution and drives the subsystems to the Pareto optimum provided infinite iterations are allowed at each sampling time. Moreover, the control for each subsystem is computed in itself without coordination layer except for a synchronization requirement between subsystems. We first introduce distributed linear systems with 2 subsystems and economic model predictive control, then show the convergence and stability properties of a suboptimal model predictive control strategy for the system.

关键词： SUB-SYSTEM control strategy predictive control Linear system line planting (agroforestry) optimal solution Economic models nonlinear model predictive control

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