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Supervisory Control of Timed State Tree Structures

Supervisory Control of Timed State Tree Structures

引用

2008 American Control Conference, Pages 441-879

作者： A. Saadatpoor C. Ma W. M. Wonham

ISBN: (纸本)9781424420780

It is well known that the nonblocking supervisory control problem is NP-hard, subject in particular to state space explosion that is exponential in the number of system components. The problem of state explosion is more challenging in Timed DES than in untimed DES. In this paper we propose to manage complexity by organizing the system as a Timed State Tree Structure (TSTS). Based on TSTS we present an efficient recursive algorithm that can perform nonblocking supervisory control design (in reasonable time and memory) for systems of state size 10~(12) and higher.

关键词： Supervisory control system component TREE STRUCTURES oversight recursive algorithms Explosions design control

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Parallel algorithms for robust convex programs over networks

Parallel algorithms for robust convex programs over networks

引用

American Control Conference

作者： Keyou You Roberto Tempo Department of Automation and TNList Tsinghua University Beijing 100084 China CNR-IEIIT Politecnico di Torino 10129 Italy

ISBN: (纸本)9781467386838

This paper proposes a parallel framework to distributedly solve robust convex programs over networks when the constraints are affected by uncertainty. To this end, we adopt a probabilistic approach based on randomly sampling the uncertainty to obtain a standard convex optimization, which is called the scenario problem. However, the number of samples to attain high levels of probabilistic guarantee of robustness may be large, which results in a large number of constraints in the scenario problem. Instead of using a single processor, we resort to multiple processors that are distributed among different nodes of a network. We study recursive algorithms which parallelize the computational task across the nodes and collaboratively solve the problem very effectively. Under local communication links, we show that each node asymptotically provides a solution to the scenario optimization problem.

关键词： Uncertainty Robustness Probabilistic logic Convex functions Optimization Complexity theory Parallel algorithms Parallel algorithms Convex function Probabilistic logic Complexity theory Robustness Uncertainty Network Uniprocessor recursive algorithms

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Constrained Kalman Filtering for IMRT Optimization

Constrained Kalman Filtering for IMRT Optimization

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2010 49th IEEE Conference on Decision and Control

作者： Isuru Dasanayake Issam El Naqa Shin Li Department of Electrical and Systems Engineering Washington University in St. Louis St. Louis MO 63130 USA Division of Bioinformatics and Outcomes Research Department of Radiation Oncology Washington University School of Medicine MO 63110 USA Faculty of Electrical and Systems Engineering Washington University in St. Louis St. Louis MO 63130 USA

ISBN: (纸本)9781424477456

In this paper, we develop a new optimization algorithm for Intensity Modulated Radiation Therapy (IMRT) planning using a dynamical systems approach. IMRT is a technique used to deliver precise radiation doses to a targeted tumor while avoiding surrounding critical structures. Modeling and optimizing an IMRT plan is a challenging task since tumors can change in size, shape, and position during the course of fractionated treatment. Accordingly, re-optimization of radiation beam weights is generally needed for each treatment fraction, which is computationally expensive and practically inefficient. We establish a recursive algorithm, which is based on the development of a constrained Kalman filter, to develop a complete treatment plan that takes changes in the tumor geometry into account. We implement this new algorithm to a model case demonstrating its robustness for IMRT planning.

关键词： Optimization algorithms Kalman filtering intensity modulated radiation therapy Tumours recursive algorithms Radiation Dosage DYNAMICAL SYSTEMS radiation beam

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Globally Optimal Kalman Filtering with Finite-Time Correlated Noises

Globally Optimal Kalman Filtering with Finite-Time Correlate...

引用

2010 49th IEEE Conference on Decision and Control

作者： Pei Jiang Jie Zhou Yunmin Zhu College of Mathematics Sichuan University Chengdu Sichuan 610064 China

ISBN: (纸本)9781424477456

In this paper, an extension of the standard Kalman filtering for the dynamical systems with white noises to finite-time correlated noises is addressed. Although one can augment the state vector with white noises in a time-variant moving average process which models the finite-time correlated noise, and then use standard Kalman filtering to obtain the optimal state estimate in the mean square error sense, a direct recursion for the optimal estimate of original state in general cases was pursued owing to the lower computational complexity. By decomposing the original Kalman gain to two recursively represented factors and increasing some recursive terms (for more than one-step correlated noises), we directly provide recursive algorithms for the globally optimal estimate of original state for stochastic linear dynamic systems with (i) multi-step correlated process noises;(ii) multi-step correlated observation noises;and (iii) multi-step correlated process and observation noises. There is no any limitation on all involved matrices in the model and algorithms. The new development for Kalman filtering is expected to further promote practical applications of dynamic system theory and methods.

关键词： Kalman filtering correlated noise white noise State estimation Mean square error recursive algorithms state vectors Dynamic systems complexity classes

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Attack Resilient State Estimation for Autonomous Robotic Systems

Attack Resilient State Estimation for Autonomous Robotic Sys...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Nicola Bezzo James Weimer Miroslav Pajic Oleg Sokolsky George J. Pappas Insup Lee PRECISE Center Department of Computer and Information Science University of Pennsylvania Philadelphia PA 19104 USA

ISBN: (纸本)9781479969357

In this paper we present a methodology to control ground robots under malicious attack on sensors. Within the term attack we intend any malicious disturbance injection on sensors, actuators, and controller that would compromise the safety of a robot. In order to guarantee resilience against attacks, we use a control-level technique implemented within a recursive algorithm that takes advantage of redundancy in the information received by the controller. We use the case study of a vehicle cruise-control, however, the strategy we present in this work is general for several applications. Our methodology relays on redundancy in the sensor measurements: specifically we consider N velocity measurements and use a recursive filtering technique that estimates the state of the system while being resilient against sensor attacks by acting on the variance of the measurements noise. Finally, we move our focus on hardware validation demonstrating our algorithm through extensive outdoor experiments conducted on two unmanned ground robots.

关键词： Sensors redundancy Ground robot recursive algorithms Controllers Noise measurement State estimation Robot

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Sensitivity Analysis of Loss Volume in Stochastic Fluid Systems with Flow Control

Sensitivity Analysis of Loss Volume in Stochastic Fluid Syst...

引用

Proceedings of the 46th IEEE Conference on Decision and Control, Pages 460-918

作者： R. Adams Y. Wardi G. Riley School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)9781424414970;1424414970

This paper concerns Infinitesimal Perturbation Analysis (IPA) for fluid queues with finite buffers, where input fluid in excess of buffer capacity is turned away and considered lost. In particular, it considers the loss-volume (and hence average loss rate) performance measure with respect to the buffer sizes. Most previous results pertained to open-loop systems, but recently there has been a mounting interest in feedback control, and especially in workload-based flow control systems. This paper considers an alternative flow-control mechanism whereby the inflow rate is restricted by an amount that is proportional to the loss rate. It first discusses a single-server queue, and then it analyzes a two-queue tandem network, while pointing out possible extensions to more general-topology networks and other performance functions. The main results are comprised of recursive algorithms for computing the IPA derivatives in nonparametric and model-free forms.

关键词： Fluid Systems flow control recursive algorithms flow control system Sensitivity analysis Isopropyl Alcohol Queue buffering capacity Induction loop systems tandem network feedback control Fluid

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Identification of a Gain System with Binary Input and Output Measurements

Identification of a Gain System with Binary Input and Output...

引用

IEEE Annual Conference on Decision and Control

作者： Keyou You Erik Weyer Girish Nair Department of Automation and TNList Tsinghua University 100084 China Department of Electrical and Electronic Engineering University of Melbourne Australia

ISBN: (纸本)9781479978878

This paper studies the identification problem of a gain system using both input and output quantized data. Specifically, the system input and the output are separately quantized into one bit before sent to a remote estimator, which generates a recursive algorithm to identify the system. If the random input is an independent and identical Gaussian process, we develop the identification algorithms respectively by using the empirical measure and the maximum likelihood estimation, which is given in a recursive form by the EM and quasi-Newton iterations. Finally, simulations are included to validate theoretical results.

关键词： binary input maximum likelihood estimation Random inputs systems input recursive algorithms Gain Output Authentication

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A constraint selection technique for set membership estimation of time-varying parameters

A constraint selection technique for set membership estimati...

引用

IEEE Annual Conference on Decision and Control

作者： Marco Casini Andrea Garulli Antonio Vicino Dipartimento di Ingegneria dell'Informazione e Scienze Matematiche Universita degli Studi di Siena via Roma 56 53100 Siena Italy

ISBN: (纸本)9781467360890

This paper presents a new recursive algorithm for approximating the feasible parameter set, in set membership estimation of time-varying parameters. The novelty of the approach lies in the use of a constraint selection technique which keeps track only of a subset of the linear constraints defining the feasible set. These are chosen as the binding constraints of suitable linear programs, that are instrumental to recursively update an orthotope containing the true feasible set. It is shown through several numerical examples that the proposed technique provides an approximation which is almost as tight as the batch minimum orthotope containing the feasible set, while its computational load is much smaller than that required to propagate the exact feasible parameter set.

关键词： time varying parameters recursive algorithms Constraint

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A REAL-TIME ALGORITHM FOR TIME DECODING MACHINES

A REAL-TIME ALGORITHM FOR TIME DECODING MACHINES

引用

European Signal Processing Conference

作者： Aurel A. Lazar Erno K. Simonyi Laszlo T. Toth Dept. of Electrical Engineering Columbia University New York NY USA Ministry of Defense Electronics Logistic and Property Management Co. Budapest Hungary Dept. of Telecom. and Media Informatics Budapest Univ. of Technology and Economics Budapest Hungary

Time-encoding is a real-time asynchronous mechanism of mapping the information contained in the amplitude of a bandlimited signal into a time sequence. Time decoding algorithms recover the signal from the time sequence. Under an appropriateNyquist-type rate condition the signal can be perfectly recovered. The algorithm for perfect recovery calls, however, for the computation of a pseudo-inverse of an infi- nite dimensional matrix. We present a simple algorithm for local signal recovery and construct a stitching algorithm for real-time signal recovery. We also provide a recursive algorithm for computing the pseudo-inverse of a family of finitedimensional matrices.

关键词： algorithms recursive algorithms Signal restoration DECODING bandlimited signals machine two-dimensional matrix timing sequence mapping information

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A NON-NEGATIVE QUADRATIC PROGRAMMING APPROACH TO MINIMIZE THE GENERALIZED VECTOR-VALUED TOTAL VARIATION FUNCTIONAL

A NON-NEGATIVE QUADRATIC PROGRAMMING APPROACH TO MINIMIZE TH...

引用

European Signal Processing Conference

作者： Paul Rodriguez Digital Signal Processing Group Pontificia Universidad Catolica del Peru

We propose a simple but flexible method for solving the generalized vector-valued TV (VTV) functional with a non-negativity constraint. One of the main features of this recursive algorithm is that it is based on multiplicative updates only and can be used to solve the denoising and deconvolution problems for vector-valued (color) images. This algorithm is the vectorial extension of the IRN-NQP (Iteratively Reweighted Norm - Non-negative Quadratic Programming) algorithm [1] originally developed for scalar (grayscale) images, and to the best of our knowledge, it is the only algorithm that explicitly includes a non-negativity constraint for color images within the TV framework.

关键词： quadratic programming color image recursive algorithms Noise reduction Television grayscale images algorithms

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