bibliography_old.bib

由matlab开发的hybrid系统的描述语言

        LOCATION           = {ethics epf-bc 6704-368 ~~~ eltech-bib c13.00.53}
}

@ARTICLE{DoPZ91,
        AUTHOR             = {Doyle, J. and Packard, A. and Zhou, K.},
        JOURNAL            = Pro30,
        PAGES              = {1227-1232},
        TITLE              = {{Review of LFTs, LMIs, and} $\mu$},
        YEAR               = {1991},
        LOCATION           = {68}
}

@INPROCEEDINGS{DoSW98,
        AUTHOR             = {Dolzmann, A. and Sturm, T. and Weispfenning, V.},
        BOOKTITLE          = KIT98,
        TITLE              = {{Real Quantifier Elimination in Practice}},
        YEAR               = {Grenoble 98},
        LOCATION           = {H5},
        SIGNATURE          = {Domenico Mignone},
        ANNOTE             = {Given a formula with \ii{quantifiers}, it is possible to eliminate the variables corresponding to those quantifiers. We do not want to repeat the details of the problem formulation, which are nicely stated in section 2 of the paper. \\

For the quantifier elimination purpose (at least) 3 techniques have been developed in the past. The software packages implementing these methods are called {\tt QEPCAD, REDLOG, and QERRC}. The focus of the paper is on {\tt REDLOG}, since the group of prof. Weispfenning has implemented this package. It is based on REDUCE, a commercial software ({\tt www.rrz.uni-koeln.de/REDUCE/}). REDLOG itself is freely available from {\tt www.fmi.uni-passau.de/$\sim$redlog}. Note also that at the homepage of REDUCE mentioned above it is possible to submit problems, without the necessity to actually buy the software. However the problem complexity seems to be rather high (doubly exponential), which might be an obstacle for many applications.\\

Some potential application fields could be optimization, scheduling or fault diagnosis. The first ideas when reading this paper were the following:
\begin{itemize}
\item {\bf Robust Control} It could be worthwhile to analyze, how a control problem with uncertainties can be set-up in order to be solved or simplified with quantifier elimination procedures.
\item {\bf Mixed Logic Dynamic Systems} Quantifier elimination could be a way of reducing the number of logical variables to introduce when modeling MLD systems. The first impression is that a combination of the MLD framework with quantifier elimination could be interesting to analyze.
\item {\bf Jim Primbs' work} The point where the application of Jim Primbs' ideas to MPC of piecewise linear systems failed, was the formulation of the cost function for a piecewise linear system in quadratic Form. The step which was easy to make for linear systems, was not immediate for p.l. systems, because we did not know a priori, which dynamics had to be used in the prediction. What if we ask for the existence of a quadratic form for the cost function and then try to eliminate the quantifiers? (J.Primbs: If you can write the cost as a quadratic, you are done...)
\end{itemize}

promising approach


}
}

@INPROCEEDINGS{DoTo95,
        AUTHOR             = {Domenjoud, E. and Tomas, A. P.},
        BOOKTITLE          = {Lecture Notes in Computer Science 976},
        PAGES              = {18-35},
        TITLE              = {{From Elliott-MacMahon to an Algorithm for General Linear Constraints on Naturals}},
        YEAR               = {1995},
        LOCATION           = {.},
        SIGNATURE          = {Domenico Mignone},
        ANNOTE             = {An old algorithm by Elliot-MacMahon (1903/1916) for solving the diophatine equation $a_1 x_1 + \dots + a_n x_n = 0$ is reviewed. Based on it, extensions are given to handle also inequalities and disequalities. \index{Elliott-MacMahon's method}}
}

@INCOLLECTION{DOTY97,
        AUTHOR             = {Daws, C. and Olivero, A. and Tripakis, S. and Yovine, S.},
        BOOKTITLE          = {Hybrid Systems III},
        NUMBER             = {1066},
        PUBLISHER          = {Springer},
        SERIES             = {Lecture Notes in Computer Science},
        TITLE              = {{The Tool Kronos}},
        YEAR               = {1997},
        LOCATION           = {177}
}

@ARTICLE{Doyl78,
        AUTHOR             = {Doyle, J.C.},
        JOURNAL            = IEEE,
        NUMBER             = {4},
        PAGES              = {756-757},
        TITLE              = {{Guaranteed Margins for LQG Regulators}},
        VOLUME             = {AC-23},
        YEAR               = {1978},
        LOCATION           = {72},
        SIGNATURE          = {Domenico Mignone},
        ANNOTE             = {There are none.}
}

@INPROCEEDINGS{dSdM98,
        AUTHOR             = {B. {De Schutter} and B. {De Moor}},
        BOOKTITLE          = {Hybrid Systems V},
        EDITOR             = {P. Antsaklis and W. Kohn and M. Lemmon and A. Nerode and S. Sastry},
        PAGES              = {70--85},
        PUBLISHER          = {Springer},
        SERIES             = lncs,
        TITLE              = {The Extended Linear Complementarity Problem and the Modeling and Analysis of Hybrid Systems},
        VOLUME             = {1567},
        YEAR               = {1999},
        isbn = {3-540-65643-X},
        topics = {lcp, hybrid},
        myref = {sista_98_40}
}

@INPROCEEDINGS{dSvdB00,
        AUTHOR             = {B. {De Schutter} and T. {van den Boom}},
        BOOKTITLE          = ACC,
        PAGES              = {4046--4050},
        TITLE              = {Model predictive control for max-plus-linear systems},
        YEAR               = {2000},
        abstract = {Model predictive control (MPC) is a very popular controller              design method in the process industry. An important advan-              tage of MPC is that it allows the inclusion of constraints on              the inputs and outputs. Usually MPC uses linear discrete-              time models. In this paper we extend MPC to a class of              discrete event systems, i.e. we present an MPC framework              for max-plus-linear systems. In general the resulting opti-              mization problem is nonlinear and nonconvex. However, if              the control objective and the constraints depend monoton-              ically on the outputs of the system, the MPC problem can              be recast as problem with a convex feasible set. If in addi-              tion the objective function is convex, this leads to a convex              optimization problem, which can be solved very efficiently.}
}

@CONFERENCE{Eber99,
        AUTHOR             = {Ebert, W.},
        BOOKTITLE          = {submitted to CDC 1999},
        TITLE              = {{Infinite Horizon Delta Domain Predictive Control}},
        YEAR               = {1999},
        DATE               = {16.5.1999},
        LOCATION           = {166},
        SIGNATURE          = {Domenico Mignone},
        ANNOTE             = {Written a review for it:

\begin{itemize}
\item The abstract should not contain any abbreviations, like RST.
\item The acronym OWGPC on page 2 is explained nowhere.
\item The value of $D(\delta)$ in equation (8) is not motivated well
 enough. Is this particular choice required or can more general values
 be chosen?
\item According to equation (8), the value of $nd$ on page 3 is 1.
 Considered that, why $nd$ is used on page 3?
\item The interpretation of equation (17) is not clear, especially
 in view that according to equation (15), $N\rightarrow \infty$.
 This means that asymptotically $R(t)$ is infinity for all $t$.
 The interpretation of this fact must be discussed.
\item Does the * in equation (18) denote complex conjugation? What is
 $\gamma^{*}$?
\item The proof of theorem 2 does not use the stabilizability and
 observability of the system, as claimed.
\item The statement of theorem 4 is not precise enough.
\item Last sentence of section 3. No difference in the results can
 be seen, even though the author claims that better results
 are achieved with one approach.
\item Too many spelling errors in the paper.
\end{itemize}

It is not clear what the new contribution of this paper consists of.
}
}

@TECHREPORT{ElBr98,
        AUTHOR             = {Elia, N. and Brandin, B.},
        INSTITUTION        = {Dept. of Electrical Engineering and Computer Science, M.I.T.},
        TITLE              = {Verification of an Automotive Active Leveler},
        YEAR               = {1998}
}

@CONFERENCE{ElCa99,
        AUTHOR             = {El Ghaoui, L. M. and Calafiore, G.},
        BOOKTITLE          = ACC99,
        NOTE               = {FA16-4},
        TITLE              = {Worst-Case State Prediction under Structured Uncertainty},
        YEAR               = {1999},
        LOCATION           = {ACC99 : FA16-4},
        ANNOTE             = {.
}
}

@MANUAL{ElDN97,
        AUTHOR             = {El Ghaoui, L. and Delebecque, F. and Nikoukhah, R.},
        MONTH              = apr,
        ORGANIZATION       = {User's Guide},
        TITLE              = {{LMITOOL: A User-Friendly Interface for LMI Optimization}},
        YEAR               = {1997},
        LOCATION           = {184},
        SIGNATURE          = {Domenico Mignone}
}

@ARTICLE{ElOA97,
        AUTHOR             = {El Ghaoui, L. and Oustry, F. and AitRami, M.},
        JOURNAL            = IEEE,
        NUMBER             = {8},
        PAGES              = {1171-1176},
        TITLE              = {{A Cone Complementarity Linearization Algorithm for Static Output-Feedback and Related Problems}},
        VOLUME             = {42},
        YEAR               = {1997},
        LOCATION           = {104}
}

@ARTICLE{Enge97,
        AUTHOR             = {Engell, S.},
        JOURNAL            = {Automatisierungstechnik},
        NUMBER             = {4},
        TITLE              = {{Modellierung und Analyse hybrider dynamischer Systeme}},
        VOLUME             = {45},
        YEAR               = {1997},
        LOCATION           = {26}
}

@ARTICLE{EzKa97,
        AUTHOR             = {Ezzine, J. and Kavranoglyu, D.},
        JOURNAL            = IJC,
        NUMBER             = {5},
        PAGES              = {1129-1146},
        TITLE              = {{On Almost-Sure Stabilization of Discrete-Time Jump Parameter Systems: an LMI Approach}},
        VOLUME             = {68},
        YEAR               = {1997},
        DATE               = {11.11.99},
        LOCATION           = {114},
        SIGNATURE          = Domi,
        ANNOTE             = {The jump linear systems change their dynamics according to a Markov chain. Criteria for almost sure stability of such systems are given.}
}

@PHDTHESIS{Fabi99,
        AUTHOR             = {Fabian, G.},
        SCHOOL             = {Technische Universteit Eindhoven},
        TITLE              = {{A Language and Simulator for Hybrid Systems}},
        YEAR               = {1999},
        DATE               = {6.10.1999},
        LOCATION           = {eltech bib C 12.20 43},
        SIGNATURE          = {Domenico Mignone},
        ANNOTE             = {The language $\chi$ can be used to describe discrete-event, continuous time and hybrid systems. In this work the hybrid $\chi$ semantics is specified. The simulator for the $\chi$ language has been extended to handle also hybrid systems. \\

$\chi$ is a concurrent language based on \ii{CSP} (Communicating Sequential Processes) for the discrete-event part and on \ii{DAE} (Differential Algebraic Equations) for the continuous part.}
}

@ARTICLE{FeAG96,
        AUTHOR             = {Feron, E. and Apkarian, P. and Gahinet, P.},
        JOURNAL            = ACC,
        TITLE              = {{S-Procedure for the Analysis of Control Systems with Parametric Uncertainties via Parameter-Dependent Lyapunov Functions}},
        YEAR               = {1996},
        DATE               = {3. 3. 1998},
        LOCATION           = {51},
        SIGNATURE          = {Domenico Mignone}
}

@INCOLLECTION{Fehn98,
        AUTHOR             = {A. Fehnker},
        BOOKTITLE          = {Hybrid Systems: Computation and Control},
        PAGES              = {110--125},
        PUBLISHER          = {Springer Verlag},
        SERIES             = {Lecture notes in Computer Science},
        TITLE              = {Automotive Control Revised - Linear Inequalities as Approximation of Reachable Sets},
        VOLUME             = {1386},
        YEAR               = {1998}
}

@ARTICLE{FeMM00,
        AUTHOR             = {Ferrari Trecate, G. and Mignone, D. and Morari, M.},
        JOURNAL            = {Proceedings of the American Control Conference},
        TITLE              = {{Moving Horizon Estimation for Piecewise Affine Systems}},
        YEAR               = {2000},
        ANNOTE             = {Moving Horizon Estimation for MLD systems. The work relies on the ideas of \cite{RaRa98}. The full information estimation problem for MLD systems is even more complex than for smooth nonlinear systems due to the presence of binary variables. Therefore the need to approximate the arrival cost is even more pronounced.\\

The estimator convergence, i.e. the notion of stability of the estimator is formulated in an asymptotic notion for the unexcited system: The moving horizon estimator is \ii{$\tau$-convergent}, if
\begin{equation}
\lim_{T \rightarrow \infty} \parallel x_{\Sigma}(T-\tau,x_0) - \hat{x}(T-\tau|T) \parallel = 0
\end{equation}
Note that contrary to the continuous time, nonlinear case in \cite{RaRa98}, the convergence is formulated for the state at the beginning of the horizon.}
}

@TECHREPORT{FeMM99,
        AUTHOR             = {Ferrari-Trecate, G. and Mignone, D. and Morari, M.},
        INSTITUTION        = {ETH Zuerich},
        TITLE              = {{Moving Horizon Estimation for Piecewise Affine Systems}},
        YEAR               = {1999},
        SIGNATURE          = Domi
}

@ARTICLE{FePa98,
        AUTHOR             = {Fenu, G. and Parisini, T.},
        JOURNAL            = ACC,
        TITLE              = {{Model-Free Fault Diagnosis for Nonlinear Systems: A Combined Kernel-Regression and Neural Networks Approach}},
        YEAR               = {1998},
        DATE               = {18.7.2000},
        LOCATION           = {201},
        SIGNATURE          = Domi,
        ANNOTE             = {
This is a model-free approach for fault detection of nonlinear discrete time systems, see \cite{FePa99} for a short summary.}
}

@ARTICLE{FePa99,
        AUTHOR             = {Fenu, G. and Parisini, T.},
        JOURNAL            = ECC,
        TITLE              = {Nonparametric Kernel Smoothing for Model-Free Fault Symptom Generation},
        YEAR               = {1999},
        DATE               = {18.7.2000},
        LOCATION