Assessment and Future Directions of Nonlinear Model Predictive ...

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Trajectory Control of Multiple Aircraft: An NMPC Approach 639[3] Asher, U. M. and Petzold, L., Computer Methods for Ordinary Differential Equationsand Differential Algebraic Equations, SIAM, 1998.[4]Betts,J.T.,Practical Methods for Optimal Control Using Nonlinear Programming,SIAM, Philadelphia, PA, 2001.[5] Biegler, L. T., Efficient Solution of Dynamic Optimization and NMPC problems,”Nonlinear Model Predictive Control, editedbyF.Allgöwer and E. Zheng,Birkhäuser, 2000, pp. 219.[6] de Nicolao, G., L. Magni, and R. Scattolini, Stability and robustness of nonlinearreceding horizon control, in Nonlinear Predictive Control, F. Allgöwer and A.Zheng, eds., vol. 26 of Progress in Systems Theory, Basel, 2000, Birkhauser, pp.3, 23.[7] Fourer, R., Gay, D., and Kernighan, B. W., A Modeling Language for MathematicalProgramming, Management Science, Vol. 36, 1990, pp. 519-554.[8] Mayne, D., Nonlinear model predictive control: Challenges and opportunities, inNonlinear Predictive Control, F. Allgöwer and A. Zheng, eds., vol. 26 of Progressin Systems Theory, Basel, 2000, Birkhäuser, pp. 23,44.[9] Nocedal,J.N.,andS.J.Wright,Numerical Optimization, Springer, Berlin (1998).[10] Raghunathan, A., V. Gopal, D. Subramanian, L. T. Biegler and T. Samad, DynamicOptimization Strategies for 3D Conflict Resolution of Multiple Aircrafts,AIAA J. of Guidance, Control and Dynamics, 27 (4), pp. 586-594 (2004).[11] Wächter, A., and L. T. Biegler, On the Implementation of an Interior Point FilterLine Search Algorithm for Large-Scale Nonlinear Programming, MathematicalProgramming, 106, 1, pp. 25-57 (2006)
Author IndexAlamir, Mazen 523Alamo, T. 131, 317Alessandri, Angelo 347Allgöwer, Frank 151, 465Alvarado, I. 317Arahal, M.R. 317Arellano-Garcia, Harvey 305Arrieta–Camacho, Juan J. 629Baglietto, Marco 347Bartusiak, R. Donald 367Barz, Tilman 305Battistelli, Giorgio 347Bemporad, A. 93Biegler, Lorenz T. 629Blank, Luise 335Bock, Hans Georg 163, 455Bogaerts, Philippe 485Bonvin, Dominique 551Bordons, Carlos 1Bravo, J.M. 131, 317Buccieri, Davide 551Camacho, Eduardo F. 1, 131, 317Cannon, Mark 255Casavola, Alessandro 581Cepeda, A. 131Chen, Hong 283Chen, Wen-Hua 565Christofides, Panagiotis D. 77Colmenares, W. 495Couchman, Paul 255Cristea, S. 495da Silva, Rui Neves 435DeHaan, Darryl 537De Keyser, Robin 503de la Peña, D. Muñoz 317De Moor, Bart 63Desa, S. 607Deshpande, Anjali 513de Prada, C. 495Diehl, Moritz 163, 455Dmitruk, Natalia M. 327Donald III, James 503Doppelhamer, Jens 399Dunbar, William B. 607Ebenbauer, Christian 151Elaiw, Ahmed M. 35El-Farra, Nael H. 77Engell, Sebastian 473Faísca, N.P. 193Famularo, Domenico 581Fiacchini, M. 131Findeisen, Rolf 283Fontes, Fernando A.C.C. 115Foss, Bjarne A. 407Franke, Rüdiger 399, 465Franzè, Giuseppe 581Fujita, Masayuki 573Gabasov, Rafail 327Gao, Xingquan 283Gatzke, Edward P. 217Grancharova, Alexandra 181Gros, Sebastien 551Grüne, L. 105Guay, Martin 537Gudi, R.D. 141
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Lecture Notesin Control and Informa
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Series Advisory BoardF. Allgöwer,
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ContentsFoundations and History of
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ContentsIXRobustness, Robust Design
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ContentsXIHybrid NMPC Control of a
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Nonlinear Model Predictive Control:
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Hybrid MPC: Open-Minded but Not Eas
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Hybrid MPC: Open-Minded but Not Eas
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22 S.E. Tuna et al.this says that i
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24 S.E. Tuna et al.In particular, f
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26 S.E. Tuna et al.W N (f(x, ¯κ N
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28 S.E. Tuna et al.where ᾱ := max
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30 S.E. Tuna et al.21.521.5µ=51
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32 S.E. Tuna et al.obstacle and gra
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34 S.E. Tuna et al.[19] C. Prieur.
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36 É. Gyurkovics and A.M. Elaiw[8]
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38 É. Gyurkovics and A.M. ElaiwWe
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40 É. Gyurkovics and A.M. ElaiwWe
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Conditions for MPC Based Stabilizat
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A Computationally Efficient Schedul
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The Potential of Interpolation for
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The Potential of Interpolation 65De
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The Potential of Interpolation 67Al
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The Potential of Interpolation 693.
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The Potential of Interpolation 71Pr
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The Potential of Interpolation 73Th
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The Potential of Interpolation 75de
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Techniques for Uniting Lyapunov-Bas
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94 M. Lazar et al.Lipschitz continu
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96 M. Lazar et al.let X T ⊆ X den
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98 M. Lazar et al.S 0 {j ∈S|0
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100 M. Lazar et al.Fig. 1. State-sp
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102 M. Lazar et al.[11] Grimm, G.,
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Model Predictive Control for Nonlin
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ReferencesModel Predictive Control
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116 F.A.C.C. Fontes, L. Magni, and
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On the Computation of Robust Contro
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142 M. Srinivasarao, S.C. Patwardha
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Numerical Methods for Efficient and
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L i (s i ,u i ):=Numerical Methods
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182 A. Grancharova, T.A. Johansen,
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194 V. Sakizlis et al.presented her
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196 V. Sakizlis et al.linear PWA fu
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198 V. Sakizlis et al.non-linear sy
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200 V. Sakizlis et al.Remark 1. For
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202 V. Sakizlis et al.One should no
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204 V. Sakizlis et al.g0.050.10.15x
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Interior-Point Algorithms for Nonli
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n p,2 ≤Interior-Point Algorithms
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Hard Constraints for Prioritized Ob
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A Nonlinear Model Predictive Contro
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Robustness and Robust Design of MPC
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MPC for Stochastic SystemsMark Cann
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y i (k) =∑n um=1MPC for Stochasti
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MPC for Stochastic Systems 259we ha
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MPC for Stochastic Systems 261form
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MPC for Stochastic Systems 263( )κ
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MPC for Stochastic Systems 265Fig.
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MPC for Stochastic Systems 267⎡
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NMPC for Complex Stochastic Systems
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284 H. Chen et al.of the moving hor
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286 H. Chen et al.Hence, at each sa
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288 H. Chen et al.control inputs in
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290 H. Chen et al.Corollary 1. The
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292 H. Chen et al.c A[mol/l]10−10
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294 H. Chen et al.[CSA97] H.Chen,C.
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296 L. Xie, P. Li, and G. Woznyand
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298 L. Xie, P. Li, and G. WoznyDeta
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300 L. Xie, P. Li, and G. Wozny3.2
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302 L. Xie, P. Li, and G. WoznyFig.
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304 L. Xie, P. Li, and G. Wozny[3]
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306 H. Arellano-Garcia et al.applic
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308 H. Arellano-Garcia et al.Fig. 1
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310 H. Arellano-Garcia et al.RECIPE
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312 H. Arellano-Garcia et al.optimi
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314 H. Arellano-Garcia et al.The re
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Interval Arithmetic in Robust Nonli
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Optimal Online Control of Dynamical
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State Estimation Analysed as Invers
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Minimum-Distance Receding-Horizon S
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New Extended Kalman Filter Algorith
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NLMPC: A Platform for Optimal Contr
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384 K. Naidoo et al.polymer control
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386 K. Naidoo et al.are two key qua
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388 K. Naidoo et al.1. It greatly s
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390 K. Naidoo et al.However, with t
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392 K. Naidoo et al.Fig. 4. Bounded
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394 K. Naidoo et al.1. Maintain pro
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396 K. Naidoo et al.7 Commissioning
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398 K. Naidoo et al.[3] N.M.C. Oliv
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400 R. Franke and J. DoppelhamerImp
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402 R. Franke and J. DoppelhamerFig
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404 R. Franke and J. DoppelhamerFig
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406 R. Franke and J. Doppelhamer[3]
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408 B.A. Foss and T.S. Scheicritica
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410 B.A. Foss and T.S. ScheiFig. 2.
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412 B.A. Foss and T.S. Scheidiscuss
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414 B.A. Foss and T.S. ScheiOther a
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416 B.A. Foss and T.S. ScheiIn the
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Integration of Economical Optimizat
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Controlling Distributed Hyperbolic
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444 K.R. Muske, A.E. Witmer, and R.
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Robust NMPC for a Benchmark Fed-Bat
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Real-Time Implementation of Nonline
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Non-linear Model Predictive Control
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NMPC of the Hashimoto Simulated Mov
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486 R. Lepore et al.In this study,
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488 R. Lepore et al.3 Control Strat
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490 R. Lepore et al.400.80.6|x−x
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492 R. Lepore et al.0.950.9w P;30.8
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Hybrid NMPC Control of a Sugar Hous
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Application of the NEPSAC Nonlinear
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Integrating Fault Diagnosis with No
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524 M. Alamirmin V (x u(·,x),T) un
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526 M. AlamirDefinition 4. The syst
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528 M. Alamir♭V is radially unbou
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530 M. AlamirBut according to the s
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532 M. AlamirFig. 2. Stabilization
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534 M. AlamirFig. 3. Closed loop be
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A New Real-Time Method for Nonlinea
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A Two-Time-Scale Control Scheme for
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566 X.-B. Hu and W.-H. Chen2 Online
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568 X.-B. Hu and W.-H. Chentime alo
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570 X.-B. Hu and W.-H. ChenFig. 3.
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572 X.-B. Hu and W.-H. ChenTable 4.
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574 M. Fujita et al. CameraCameraTa
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576 M. Fujita et al.J(u, t) =∫t+T
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578 M. Fujita et al.ξ 2[rad/s]6420
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580 M. Fujita et al.Acknowledgement
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582 A. Casavola, D. Famularo, and G
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