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Fast implementations and rigorous models: Can both be accommodated in NMPC?

INTERNATIONAL JOURNAL OF ROBUST AND nonlinear control 2008年第8期18卷 800-815页

作者： Zavala, Victor M. Laird, Carl D. Biegler, Lorenz T. Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

In less than two decades, nonlinear model predictive control has evolved from a conceptual framework to an attractive, general approach for the control of constrained nonlinear processes. These advances were realized both through better understanding of stability and robustness properties as well as improved algorithms for dynamic optimization. This study focuses on recent advances in optimization formulations and algorithms, particularly for the simultaneous collocation-based approach. Here, we contrast this approach with competing approaches for online application and discuss further advances to deal with applications of increasing size and complexity. To address these challenges, we adapt the real-time iteration concept, developed in the context of multiple shooting (Real-Time PDE-Constrained Optimization. SIAM: Philadelphia, PA, 2007;25-52, 3-24), to a collocation-based approach with a full-space nonlinear programming solver. We show that straightforward sensitivity calculations from the Karush-Kuhn-Tucker system also lead to a real-time iteration strategy, with both direct and shifted variants. This approach is demonstrated on a large-scale polymer process, where online calculation effort is reduced by over two orders of magnitude. Copyright (c) 2007 John Wiley & Sons, Ltd.

关键词： nonlinear model predictive control nonlinear programming collocation finite elements sensitivity analysis

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A New Fast NMPC Scheme for Parallel Kinematic Manipulators: Design and Real-Time Experiments

A New Fast NMPC Scheme for Parallel Kinematic Manipulators: ...

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Signal, control and Communication (SCC), International Conference on

作者： Rihab Kouki Ahmed Chemori Faouzi Bouani LR11ES20 Laboratoire Analyse Conception et Commande des Systémes Université de Tunis El Manar Ecole Nationale d’Ingénieurs de Tunis Tunis Tunisie Laboratoire d’Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) Univ. Montpellier - CNRS Montpellier France

ISBN: (数字)9781728135960

ISBN: (纸本)9781728135977

This paper adresses the design of a new extension of fast nonlinear model predictive control (NMPC) for parallel manipulators. The developed controller is based on a parameterized NMPC, a fast gradient solver and a proportional derived controller (PD). The main motivation behind the proposed approach is to improve the tracking performance of fast parallel manipulators and reduce the computation time per control iteration. This control scheme is faster, in terms of computing time, than the classical NMPC and ensures the robustness of the resulting closed-loop system. To demonstrate the effectiveness of the proposed controller, real-time experiments are performed on a 4-DOF parallel kinematic manipulator called VELOCE.

关键词： computational time Manipulators Fasting visual tracking Parallel Lines kinematics nonlinear model predictive control controllers

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A predictive control Design with Speed Previewing Information for Vehicle Fuel Efficiency Improvement

A Predictive Control Design with Speed Previewing Informatio...

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American control Conference

作者： Mehmet Fatih Ozkan Yao Ma Department of Mechanical Engineering Texas Tech University Lubbock Texas

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

The growing vehicle connectivity and autonomy in the ground transportation system are not only able to improve traffic safety but also fuel efficiency. This paper proposes a computational friendly receding-horizon optimization-based nonlinear model predictive control (NMPC) algorithm to achieve fuel-saving speed planning for connected vehicles. The NMPC method solves for the fuel-optimal speed profile of connected vehicles considering a short speed preview of the preceding vehicle. By utilizing such previewing information through vehicle connectivity, the fuel consumption of the connected vehicles is reduced by avoiding unnecessary braking and acceleration, particularly in transient operating conditions. In order to analyze the effectiveness of NMPC design, dynamic programming (DP) method is adopted as a benchmark algorithm where the full speed preview of the preceding vehicle is known. The performances of NMPC and DP designs in driving behavior and fuel economy are quantitatively explored and compared under several standard driving cycles. Results show a promising improvement of the performance by adopting the proposed design and reveal the potential fuel benefits brought by vehicle connectivity and autonomy.

关键词： vehicle Autonomy Fuel efficiency design control transport system Driver Behavior Traffic safety nonlinear model predictive control Fuel economy Operating conditions predictive control

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Error-triggered on-line model identification in economic model predictive control

Error-triggered on-line model identification in economic mod...

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American control Conference

作者： Anas Alanqar Helen Durand Panagiotis D. Christofides Department of Chemical and Biomolecular Engineering University of California Los Angeles 90095 USA Department of Chemical and Biomolecular Engineering and the Department of Electrical Engineering University of California Los Angeles 90095 USA

ISBN: (纸本)9781467386838

Economic model predictive control (EMPC) is a feedback control technique that employs real-time dynamic optimization to find optimal control actions with respect to a cost function representing the plant economics. The model used in EMPC must be able to capture the important dynamics of the plant. In industry, it may be difficult in many applications to obtain a first-principles model of the process, in which case a linear empirical model constructed using process data may be used as the process model within an EMPC. However, linear empirical models may not capture the nonlinear dynamics over a wide region of state-space, restricting an EMPC to operate in a small region within which the potential of EMPC for improving process profit is not realized. For this reason, we present a scheme for expanding the level sets used to design state constraints in Lyapunov-based economic model predictive control (LEMPC) with linear empirical models to improve the process profit, incorporating on-line updates of the linear empirical model triggered by model prediction errors quantified by a moving horizon error detector. A chemical process example illustrates that the proposed LEMPC can maintain closed-loop stability of the process and bring the performance close to that which would be obtained if the nonlinear process model were used in LEMPC.

关键词： predictive models Economics Mathematical model Level set predictive control Optimization predictive control Level set Prediction models economics model identification procedural model Mathematical model Economic models EMPC on-line model distributed model predictive control nonlinear model predictive control Cost functions

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Autonomous Bike System for Acrobatic Motions

Autonomous Bike System for Acrobatic Motions

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SICE Annual Conference

作者： Yusuke Igarashi Masaki Yamakita Department of Control and Systems Engineering Tokyo Institute of Technology Tokyo Japan Department of System and Control Engineering Tokyo Institute of Technology Tokyo Japan

In this paper, we consider a bike robot model using a balancer with a flywheel which performs a wheelie movement and quick turn. By rotating a flywheel balancer back and forth, it is possible to stabilize the bike robot. Also, by swinging the balancer forward, the wheelie motion can be generated, and by performing the wheelie action, the constraint between the front wheel and the ground disappears, and a sudden turning operation is possible with the rear wheel as a joint. We construct a control system using nonlinear model predictive control, C / GMRES method, in which discontinuities of the state variables are considered. The feasibility of direction change using the wheelie motion is verified by a numerical simulation.

关键词： Bike robot nonlinear model predictive control C / GMRES method

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model predictive control for the Operation of Building Cooling Systems

Model Predictive Control for the Operation of Building Cooli...

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American control Conference

作者： Yudong Ma Francesco Borrelli Brandon Hencey Brian Coffey Sorin Bengea Philip Haves Department of Mechanical Engineering University of California Berkeley CA 94720-1740 USA United Technologies Research Center East Hartford Connecticut USA Department of Architecture University of California Berkeley CA 94720-1740 USA Lawrence Berkeley National Lab USA

ISBN: (纸本)9781424474264

A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reduction in the central plant electricity cost and improvement of its efficiency.

关键词： Buildings model predictive control COOLING SYSTEM Refrigeration equipment Storage Tanks water-tanks CHILLER nonlinear model predictive control predictive control building load central plant Load modeling

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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...

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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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model predictive control of a high speed switched reluctance generator system

Model predictive control of a high speed switched reluctance...

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European control Conference

作者： Sava Marinkov Bram de Jager Maarten Steinbuch Department of Mechanical Engineering Eindhoven University of Technology

ISBN: (纸本)9781479901890

This paper presents a novel voltage control strategy for the high-speed operation of a Switched Reluctance Generator. It uses a linear model predictive control law based on the average system model. The controller computes the DC-link current needed to achieve the tracking of a desired voltage reference in the presence of an unknown electrical load current. Its output is converted into a pair of excitation angles (turn-on/turn-off) by means of optimized scaling and mapping, while minimizing the dominant high-speed power loss. The constraints on the average DC-link voltage and current signals are directly handled. A numerical example is provided to validate the effectiveness and the robustness of the proposed control scheme.

关键词： Reluctance generators predictive control voltage reference High-speed operation DC link model predictive control distributed model predictive control nonlinear model predictive control numerical example High speed control law

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Robust model predictive control of a Laboratory Two-Tank System

Robust Model Predictive Control of a Laboratory Two-Tank Sys...

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American control Conference

作者： Monika Bakosova Juraj Oravec Faculty of Chemical and Food Technology Slovak University of Technology in Bratislava Radlinskeho 9 812 37 Bratislava Slovakia

ISBN: (纸本)9781479932757

Robust model predictive control was applied for the laboratory two-tank system. The controlled process is modeled as the uncertain polytopic system for the controller design. Two robust model predictive control design strategies were used. The first strategy uses the single Lyapunov function and the second one assumes the parameter-dependent Lyapunov functions. The design problem is converted to the solution of the system of linear matrix inequalities and a simple algorithm is also presented. The controllers designed using both strategies were tested on the laboratory process. The results confirmed that using the parameter-dependent Lyapunov function in the robust model predictive controller design improved the control performance in comparison with the single Lyapunov function based strategy.

关键词： Liapunov function nonlinear model predictive control model predictive control predictive control design problems control performance controller design controllers linear matrix inequalities

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A model predictive control Approach to Attitude Stabilization and Trajectory Tracking control of a 3D Universal Joint Space Robot with an Initial Angular Momentum

A Model Predictive Control Approach to Attitude Stabilizatio...

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IEEE Conference on Decision and control

作者： Tatsuya Kai Faculty of Information Science and Electrical Engineering Kyushu University JAPAN

ISBN: (纸本)9781612848006

In this paper, we deal with two types of control problems for a 3D space robot of two rigid bodies with an initial angular momentum. In our previous work, we studied a near-optimal control approach to the state transition control problem for the 3D space robots with initial angular momenta. However, for the approach, we need huge computation amount and other control purposes cannot be treated. In order to overcome these disadvantages, in this paper we apply model predictive control to the attitude stabilization control problem and the trajectory tracking control problem for a 3D universal joint space robot with an initial angular momentum. As a results of simulations, we can see that both attitude stabilization control and trajectory tracking control for the 3D space robot are accomplished by the model predictive control approach. Moreover, it can be also confirmed that this approach considerably reduces computation amount and achieves real-time control of the 3D space robot.

关键词： aerospace robotics trajectory tracking predictive control attitude stabilisation Joint space tracking control Rigid bodies Real time control Standing Orders nonlinear model predictive control Three Dimensions Robot

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