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

共 1663 条记录，以下是1641-1650 订阅

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model predictive control for an Unmanned Helicopter

Model Predictive Control for an Unmanned Helicopter

引用

IEEE International Conference on Unmanned Systems (ICUS)

作者： Xing Gong BeijingAerospace Feiteng Equipment Technology Co. LTD ChinaAerospace Science and Technology Corporation Beijing China

ISBN: (纸本)9781728137933

Helicopter is a very interesting MIMO plant with strong nonlinearity and coupling properties. This article implements a controller for helicopter based on the cascade control strategy. A discrete model predictive controller(DMPC) using Laguerre functions is proposed for velocity tracking, and an active disturbance rejection controller is presented for attitude stabilization. The exponentially data weighting method is introduced into DMPC design to overcome the numerical instability caused by a large prediction horizon. In addition, a prescribed degree of closed-loop stability is adopted to obtain satisfying closed-loop performance and ease the difficulty of parameter tuning. Finally, the simulation with wind disturbance demonstrates the effectiveness of the controller.

关键词： Discrete model predictive control Exponentially data weighting Prescribed degree of stability Active disturbance rejection control drone helicopters distributed model predictive control Robust control Helicopters Dimyristoylphosphatidylcholine controllers Laguerre functions model predictive control predictive control nonlinear model predictive control cascade control closed-loop performance

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Plug-and-Play model predictive control for Electric Vehicle Charging and Voltage control in Smart Grids

Plug-and-Play Model Predictive Control for Electric Vehicle ...

引用

IEEE Annual Conference on Decision and control

作者： Somil Bansal Melanie N. Zeilinger Claire J. Tomlin Department of Electrical Engineering and Computer Sciences University of California at Berkeley Berkeley CA 94720 USA

ISBN: (纸本)9781467360890

This paper presents a predictive controller for handling plug-and-play (P&P) charging requests of electric vehicles (EVs) in a distribution system. The proposed method uses a two-stage hierarchical control scheme based on a model predictive control (MPC) formulation for tracking periodic references. The first stage computes a reachable periodic reference that trades off deviation from the nominal voltage with the required generation control. The second stage computes a controller that tracks this reference and charges the EVs, while satisfying system constraints at all times. Under the assumption of a time-periodic load, it is shown that the proposed controller is recursively feasible and exponentially stable i.e. the EVs' state of charge (SOC) and bus voltages converge to the desired SOC and to the optimal periodic reference respectively. Finally, the proposed scheme is illustrated in a set of examples.

关键词： Electric vehicles Smart grids Voltage regulation Plug and play predictive control Nominal Voltage predictive controllers exponential stability. model predictive control controllers dispensing system nonlinear model predictive control Periodic disorientation to time

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Experimental Research on model predictive control of 3-level 4-leg Flying Capacitor Converter Operating as Shunt Active Power Filter

Experimental Research on Model Predictive Control of 3-level...

引用

Annual Conference of the IEEE Industrial Electronics Society

作者： Kamil Antoniewicz Marek Jasinski Marian P. Kazmierkowski Mariusz Malinowski Institute of Control and Industrial Electronics Warsaw University of Technology Koszykowa 75 00-662 Warsaw

ISBN: (纸本)9781479917631

In this paper model predictive control (MPC) with finite control states set (FS) is proposed as the new control approach for 3-level 4-leg Flying Capacitor Converter (FCC) operating as a Shunt Active Power Filter (SAPF). The main concerns and solutions regarding the algorithm development and experimental studies are described. The first is addressed to the modeling of the 4-wire SAPF and 3-level 4-leg FCC. The second relates to the control of Flying Capacitors voltages, which is performed outside the prediction loop. The issue regarding undesirable transitions of switching states is described and the solution to eliminate it is shown. Also, an analysis of possible delays on laboratory model is performed and the compensation method is presented. Finally, the control performance was tested experimentally on the 10 kVA FCC laboratory model and the results are shown in the last section.

关键词： active power filter compensation method Flying Capacitors model predictive control predictive control power filters Federal Communications Commission (FCC) convener operations shunt Shunts (electrical) distributed model predictive control nonlinear model predictive control control performance Solutions

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Simulated Annealing-Particle Swarm Optimization (SA-PSO): Particle Distribution Study and Application in Neural Wiener-based NMPC

Simulated Annealing-Particle Swarm Optimization (SA-PSO): Pa...

引用

Asian control Conference

作者： S. Sudibyo M. N. Murat N. Aziz Mineral Processing Division Indonesian Institute of Science (LIPI) School of Chemical Engineering Engineering Campus Universiti Sains Malaysia

ISBN: (纸本)9781479978632

Good nonlinear optimization plays a vital role in advanced controller such as nonlinear model predictive control (NMPC). Particle swarm optimization (PSO) is one of nonlinear optimization which has a good potential to be implemented in the NMPC. Even though PSO can determine global optimum value, it is less superior in determining a local minimum value. Meanwhile, another optimizer known as simulated annealing (SA), has an opposite capability of PSO in determining the local and global values. Consequently, in this work, the SA and PSO optimizers have been combined to form SA-PSO which expected to cater both local and optimum point searching. From the particle distribution study, the result shows that the SA-PSO has better particle distribution than the original PSO. The proposed SA-PSO optimizer has also successfully applied in NMPC to control temperatures in the MTBE reactive distillation. The set point tracking test show that the NMPC using SA-PSO have good performance with small amount of overshoot, low settling time and small amount of error.

关键词： Simulated annealing optimization PSO nonlinear model predictive control Neural Wiener

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model predictive control for randomly switching max-plus-linear systems using a scenario-based algorithm

Model predictive control for randomly switching max-plus-lin...

引用

2010 49th IEEE Conference on Decision and control

作者： Ton van den Boom Bart De Schutter Delft Center for Systems and Control Delft University of Technology Mekelweg 2 2628 CD Delft The Netherlands

ISBN: (纸本)9781424477456

Switching max-plus-linear (SMPL) systems are discrete event systems that can switch between different modes of operation. In each mode the system is described by a max-plus-linear state equation and a max-plus-linear output equation, with different system matrices for each mode. The switching between from one mode to the other is a stochastic process. In the model predictive control (MPC) formulation stability is enforced by additional constraints. To reduce the computational complexity we use an algorithm based on scenario generation for such stochastic SMPL systems.

关键词： model predictive control predictive control operation mode Linear system equations of state switching discrete event systems Markov chain complexity classes redundant constraint nonlinear model predictive control

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Robust Output Feedback model predictive control for Linear Systems via Moving Horizon Estimation

Robust Output Feedback Model Predictive Control for Linear S...

引用

2008 American control Conference, Pages 441-879

作者： D. Sui L. Feng M. Hovd Department of Engineering Cybernetics Norwegian University of Science and Technology Norway 7491

ISBN: (纸本)9781424420780

This paper provides a simple approach to the problem of robust output feedback model predictive control (MPC) for linear systems with state and input constraints, subject to bounded state disturbances and output measurement errors. The problem of estimating the state is addressed by using moving horizon estimation (MHE). For such an MHE estimator, it is shown that the state estimation error converges and stays in some set, which is taken into account in the design of the output feedback MPC controllers. In the MPC formulation where the nominal system is considered, the constraints are tightened in a monotonic sequence such that satisfaction of the input and state constraints is guaranteed. Robust stability of an invariant set for the closed-loop original system is ensured. The performance of the approach is assessed via a numerical example.

关键词： model predictive control Moving horizon estimation Constrained linear systems with bounded disturbances Linear system model predictive control predictive control Output feedback Moving horizon state estimation nonlinear model predictive control Error measure Horizon Robust stability pull rope

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Linear model predictive control for a cascade ODE-PDE system

Linear model predictive control for a cascade ODE-PDE system

引用

American control Conference

作者： Seyedhamidreza Khatibi Guilherme Ozorio Cassol Stevan Dubljevic Department of Chemical & Materials Engineering University Of Alberta Canada

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

This manuscript addresses the design of a model predictive controller for a system of coupled ODE-PDE equations. The ODE describes a simple CSTR dynamics and the output of this system is coupled to the entrance of convection-diffusion reactor. The proposed controller is able to optimize the system performance while being able to handle input constraint and stabilize the system. As a discrete representation of the system is necessary, this is achieved by the application of structure preserving Cayley-Tustin time discretization to the coupled ODE-PDE system, without the use of spatial approximations or order reduction. Finally, the simulation results show the controller performance with and without constraints by comparing the results with the open-loop response.

关键词： nonlinear model predictive control Reduced order model predictive control predictive controllers System performance linear models cascades entry controllers time-discrete

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model predictive control based on Finite Impulse Response models

Model Predictive Control based on Finite Impulse Response Mo...

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2008 American control Conference, Pages 441-879

作者： Guru Prasath John Bagterp Jorgensen Informatics and Mathematical Modelling Technical University of Denmark DK-2800 Kgs. Lyngby Denmark

ISBN: (纸本)9781424420780

We develop a regularized l_(2) finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l_(2) MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC.

关键词： IMPULSE RESPONSE predictive controllers nonlinear model predictive control model predictive control predictive control simulating Finite

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model predictive tracking control for wheeled mobile robots based on polytopic linear differential inclusion

Model predictive tracking control for wheeled mobile robots ...

引用

第三十九届中国控制会议

作者： Peng Li Ling Zhao Hongjiu Yang Shizhan Wang Shuaiying Wang School of Electrical and Information Engineering Tianjin University State Key Laboratory of Precision Measuring Technology and Instruments Tianjin University

In this paper, a nonlinear model predictive control scheme is developed to achieve trajectory tracking for a wheeled mobile robot. A polytopic linear differential inclusion(PLDI)-based method is introduced in the control scheme to obtain a suitable terminal penalty term and a corresponding terminal region. By the PLDI-based method, some linear matrix inequality conditions are given to design the terminal region. Furthermore, recursive feasibility and convergence are investigated for the nonlinear model predictive control scheme. Effectiveness of the proposed scheme is demonstrated by simulation results.

关键词： Wheeled mobile robot Trajectory tracking nonlinear model predictive control Polytopic linear differential inclusion Feasibility and convergence

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Computational Aspects of Distributed Optimization in model predictive control

Computational Aspects of Distributed Optimization in Model P...

引用

IEEE Annual Conference on Decision and control

作者： Christian Conte Tyler Summers Melanie N. Zeilinger Manfred Morari Colin N. Jones Automatic Control Laboratory Department of Information Technology and Electrical Engineering ETH Zurich Automatic Control Laboratory Ecole Polytechnique Federale de Lausanne (EPFL)

ISBN: (纸本)9781467320658

This paper presents a systematic computational study on the performance of distributed optimization in model predictive control (MPC). We consider networks of dynamically coupled systems, which are subject to input and state constraints. The resulting MPC problem is structured according to the system's dynamics, which makes the problem suitable for distributed optimization. The influence of fundamental aspects of distributed dynamic systems on the performance of two particular distributed optimization methods is systematically analyzed. The methods considered are dual decomposition based on fast gradient updates (DDFG) and the alternating direction method of multipliers (ADMM), while the aspects analyzed are coupling strength, stability, initial state, coupling topology and network size. The methods are found to be sensitive to coupling strength and stability, but relatively insensitive to initial state and topology. Moreover, they scale well with the number of subsystems in the network.

关键词： model predictive control predictive control Distribute INITIAL CONDITIONS Dynamic systems System dynamics System performance Maximum Allowable Concentration Optimization methods SUB-SYSTEM distributed model predictive control nonlinear model predictive control topology

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