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

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Trajectory replanning in V2V lane exchanging with consideration of driver preferences

Trajectory replanning in V2V lane exchanging with considerat...

引用

American control Conference

作者： Jinxiang Wang Junmin Wang Rongrong Wang School of Mechanical Engineering at Southeast University Nanjing 211189 China Department of Mechanical and Aerospace Engineering at The Ohio State University Columbus 43210 USA

ISBN: (纸本)9781467386838

This paper presents a trajectory replanning control method for semi-autonomous vehicle to vehicle (V2V) systems. A trajectory generating model for lane-changing maneuver is integrated into the driver-vehicle system. Based on this system, both risk of collision and lane-exchanging intentions of the drivers can be considered in the trajectory replanning. A model predictive control (MPC) with parameters of a discretized nonlinear system is proposed to realize the optimization objectives of satisfying the drivers' maneuvering intentions and reducing the collision risk. The optimization problem is subject to the constraints consisting of human driver preferences, driving habits, and driving ability of the drivers. Simulations are conducted to verify the validity of the MPC controller and to demonstrate the controller's performance and robustness for the reduction of collision risk in scenarios of different initial conditions. The results show that the proposed controller can satisfy drivers' intentions while avoiding collision.

关键词： driver intention Vehicle to Vehicle collision avoidance model predictive control trajectory replanning V2V collision risk Collision avoidance Drivers predictive control driver circuits trajectory model predictive control distributed model predictive control nonlinear model predictive control driving skill Lane changing controllers

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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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model predictive control of Burgers Equation Based on Galerkin models

Model Predictive Control of Burgers Equation Based on Galerk...

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American control Conference

作者： Mathias Hakenberg Dirk Abel Faculty of Mechanical Engineering RWTH Aachen University 52074 Aachen Germany

ISBN: (纸本)9781479901777

A feedback control design for Burgers equation is proposed using a model predictive control approach. A low-order POD Galerkin model derived from a numerical simulation of Burgers equation is used as internal controller model. The reduced-order model accurately predicts the system dynamics as a function of the actuated Dirichlet boundary condition. Closed-loop simulations for reference tracking of a single point inside the computational domain are shown for the ideal case and also in the presence of additional disturbance and measurement noise.

关键词： actuated computational presence burger Burger equation predictive control System dynamics Equation model predictive control distributed model predictive control nonlinear model predictive control Noise measurement single turnout

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model predictive control of interleaved dc-dc stage for photovoltaic microconverters

Model predictive control of interleaved dc-dc stage for phot...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Jaime W. Zapata Samir Kouro Matias Aguirre Thierry Meynard Electronics Engineering Department Universidad Tecnica Federico Santa Maria Institut National Polytechnique de Toulouse University of Toulouse

ISBN: (纸本)9781479917631

The development of different configurations and topologies implemented in photovoltaic (PV) plants have made possible the increase of efficiency of the system. The traditional configurations of grid-connected PV systems, centralized, string, multi-string and ac-module, have been analyzed and actually most of them are controlled using classic PI control. Furthermore, each of them has different efficiency values due to the inherent associated problems. The large-scale PV plants do not work properly when the modules do not work at the same conditions, for example when some atmospheric and environmental problems are involved, it reduces the reliability of the system. The traditional small-scale PV configurations have a low efficiency due to the dc-boosting stage in order to reach the grid levels. This work presents a grid-connected PV configuration, focused in the improve of the efficiency of the traditional ac-module configuration, a flyback topology for the dc-side and a H-bridge topology for the grid connection will be implemented. Moreover, the proposed control scheme is based on FCS-MPC algorithm.

关键词： Polydnaviridae topology PHOTOVOLTAIC configurations model predictive control predictive control Grid computing distributed model predictive control nonlinear model predictive control DC side

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Simultaneous Optimization of Dispatching and Routing for OHT Systems via Hybrid System modeling

Simultaneous Optimization of Dispatching and Routing for OHT...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Ryosuke Nakamura Kenji Sawada Seiichi Shin Kenji Kumagai Hisato Yoneda Department of Mechanical Engineering and Intelligent Systems The University of Electro-Communications Murata machinery Ltd

ISBN: (纸本)9781479902255

This paper proposes a new static simultaneous optimization of dispatching and conflict-free routing for unidirectional Overhead Hoist Transport (OHT) systems. Our objective is to minimize the entire transportation time where the given transportation tasks are finished. A hybrid system modeling is applied for OHT system that is constituted by the OHT vehicles at the lower level and governed by the upper level scheduler. In the proposed modeling, it is clarified that the simultaneous optimization problems are recast as a binary integer linear problem by using model predictive control. This paper presents a numerical example and discusses limitation of proposed modeling.

关键词： Overhead Hoist Transport system Simultaneous optimization Dispatching Routing Hybrid system model predictive control Dispatching hybrid systems Network routing model predictive control predictive control distributed model predictive control nonlinear model predictive control modeling

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A Flexible Low Cost Embedded System for model predictive control of Industrial Processes

A Flexible Low Cost Embedded System for Model Predictive Con...

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European control Conference

作者： Daniel M. Lima Marcus V. Americano da Costa Julio E. Normey-Rico Department of Automation and Systems Federal University of Santa Catarina

ISBN: (纸本)9781479901890

model predictive control is an algorithm commonly used in the petrochemical and chemical sectors to control large processes. Its success can be traced to the fact that it is MIMO control algorithm with intrinsic dead-time compensation, capacity to handle the process constraints and with tuning parameters that are easily understandable in the time domain. Nevertheless, its usage is limited to large processes where the investment in the currently expensive advanced control systems are economically viable. Thus, this work proposes a low cost embedded MPC controller targeted at companies with medium and small processes that could have production improvements with the use of MPC. This paper details the current embedded system prototype and the results obtained with a hardware-in-the-loop experiment of an ethanol distillation process simulator.

关键词： Embedded systems model predictive control predictive control distributed model predictive control nonlinear model predictive control Industrial processes Petrochemicals Maximum Allowable Concentration TIME-DOMAIN Companies

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distributed MPC with parametric coordination

Distributed MPC with parametric coordination

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American control Conference

作者： Pavel Trnka Vladimir Havlena Jaroslav Pekar Honeywell ACS Global Laboratory Prague V Parku 2326/18 148 00 Czech Republic

ISBN: (纸本)9781467386838

The paper presents an effective coordination scheme for a distributed optimization based on dual decomposition. The targeted class of optimization problems are strictly convex quadratic functions with linear constraints, where the dual function with coupling equality constraints in Lagrangian is continuous piecewise quadratic. The coordination is based on multi-parametric programming - the subproblem solvers return their solution on a polyhedron around a given Lagrange multiplier value. Centralized coordinator constructs the gradient and Hessian of a dual function and reaches exact consensus in a finite number of iterations, while only some subproblems are queried for a new solution in each iteration. The algorithm is applied to the distributed model predictive control. The efficiency, in terms of optimization time and the number of iterations, is demonstrated on the distributed model predictive control of the Barcelona water distribution network.

关键词： Optimization Couplings predictive control Newton method Prediction algorithms distributed algorithms Prediction algorithms distributed algorithms predictive control Newton method Couplings distributed model predictive control BIFUNCTIONAL iterative methods coupling polyhedrons Hessian

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Robust tube based model predictive control for constrained systems with dead-time

Robust tube based model predictive control for constrained s...

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UKACC International Conference on control 2010

作者： Tito L. M. Santos Daniel Limon Teodoro Alamo Julio E. Normey-Rico Departamento de Automação Sistemas Universidade Federal de Santa Catarina Florianopolis Santa Catarina Brazil Departamento de Ingeniería de Sistemas y Automática Sevilla Spain

ISBN: (纸本)9781627481199

Computational demand is one of the most important issues in robust model predictive control (RMPC). Although RMPC strategies can be applied directly to control dead-time systems, by using usual approach, state-space representation order depends on the dead-time length which may lead to prohibitive implementation aspects. This paper proposes a explicit dead-time compensation strategy for tube based MPCs in order to use a delay free state-space representation. It is shown that explicit compensation is equivalent to the state-space augmentation if the robust constraints are suitable chosen.

关键词： Dead-Time Compensator Robust control model predictive control Constrained linear Systems Stability DEAD TIME model predictive control predictive control State-space Representation distributed model predictive control nonlinear model predictive control Explicit time system

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Automatic Landing of a UAV using model predictive control for the surveillance of Internal Autopilot's controls

Automatic Landing of a UAV using Model Predictive Control fo...

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International Conference on Unmanned Aircraft Systems

作者： Juliano A. de Bonfim Gripp Ulisses P. Sampaio Instituto Tecnologico de Aeronautica

ISBN: (纸本)9781479923779

Recent advancements in processing capabilities have enabled the possibility of use of new computationally costly control methods like the model predictive control (MPC) on real-time applications. On this paper, a framework is proposed for the design of a supervising MPC to be implemented over a simpler, more reliable internal loop PID Autopilot without making any modifications to its structure. The proposed system was able to add new capabilities to the internal loop by making little corrections to its control demands, ensuring the compliance with restrictions. At the end, the system was able to ensure safe landing over many demanding conditions by effectively expanding the internal autopilots states and by enforcing altitude restrictions.

关键词： Automatic pilots Autoland model predictive control predictive control cage set real-time application program distributed model predictive control nonlinear model predictive control Unmanned Aerial Vehicle drone honey bees Internal control Methods Maximum Allowable Concentration

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model predictive control of Autonomous Underwater Vehicles Based on the Simplified Dual Neural Network

Model Predictive Control of Autonomous Underwater Vehicles B...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Zheng Yan Siu Fong Chung Jun Wang Department of Mechanical and Automation Engineering The Chinese University of Hong Kong

ISBN: (纸本)9781467317139

Based on a recurrent neural network, a model predictive control (MPC) method for control of a class of autonomous underwater vehicles (AUVs) is presented. A coupled nonlinear kinematic model with constrains is considered. The model predictive control problem of AUVs is formulated as a time-varying quadratic programming problem, and a one-layer recurrent neural network called the simplified dual network is applied for real-time optimization. It is able to converge to the global optimal solution of the constrained optimization problem. Simulation results are discussed to demonstrate the effectiveness and characteristics of the proposed model predictive control method.

关键词： Autonomous underwater vehicles model predictive control Real-time optimization Autonomous underwater vehicles predictive control model predictive control recurrent neural nets underwater vehicles distributed model predictive control nonlinear model predictive control quadratic programming dual network

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