Proceedings of the 2011 American Control Conference最新文献

{"title":"Reconstruction of topologies for acyclic networks of dynamical systems","authors":"D. Materassi","doi":"10.1109/ACC.2011.5991335","DOIUrl":"https://doi.org/10.1109/ACC.2011.5991335","url":null,"abstract":"The paper deals with the problem of unveiling the link structure of a network of linear dynamical systems. A technique is provided guaranteeing the exact detection of the links for networks with no undirected cycles (Linear Dynamic Polytrees). The result extends previous work that was limited to a more restricted class (Linear Cascade Model Trees).","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122631053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linear programming based routing design for a class of positive systems with piecewise constant capacity constraints","authors":"Heather M. Arneson, Cédric Langbort","doi":"10.1109/ACC.2011.5991567","DOIUrl":"https://doi.org/10.1109/ACC.2011.5991567","url":null,"abstract":"We present a technique to design routing parameters for positive compartmental conservative systems with capacity constraints. Such systems describe the flow of material through a network of interconnected reservoirs and have become popular, in particular, as models of air traffic flows. The technique presented here is a Linear Programming based method to design time varying routing parameters to satisfy piecewise constant capacity constraints. Under these routing parameters, the resulting system is positive, conservative and exhibits the desired interconnection.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122846294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The matching coefficients PID controller","authors":"A. S. Hauksdóttir, S. Sigurðsson","doi":"10.1109/ACC.2011.5990764","DOIUrl":"https://doi.org/10.1109/ACC.2011.5990764","url":null,"abstract":"The problem of designing a PID controller is posed in a setting where a selected reference system presents the design requirements. This leads to a simple problem of equating coefficients of like powers in polynomials originating in the reference system transfer function, the transfer function of the system to be controlled as well as the PID coefficients. Effectively, an overdetermined system of equations in the PID coefficients results, which is solved in the minimum least squares sense. We refer to this controller as the Matching Coefficients PID (MC PID). The computation is very simple involving only basic high school mathematics. While there is no explicit criterion for a selection of a reference system that will guarantee closed loop stability, systematic approaches can be designed for modifying the reference system in these cases.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122906745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An algebraic approach to design observers for delay-independent stability of systems with single output delay","authors":"Payam Nia, R. Sipahi","doi":"10.1109/ACC.2011.5991327","DOIUrl":"https://doi.org/10.1109/ACC.2011.5991327","url":null,"abstract":"This paper presents an algebraic approach to design the control law of a LTI observer used to stabilize a LTI plant with an output delay. Different than the existing work, we use the observer gains to influence the plant stability. This becomes possible simply by removing the delay terms from the observer part. Given the plant controller gains, our approach can find the parametric regions with respect to the observer controller gains so that gains selected from these regions make the combined plant-observer system asymptotically stable independent of the amount of delay in the plant. An example with simulations is provided to demonstrate the advantages of the proposed observer design.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"260 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122928866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data driven inverse-model control of SI engines","authors":"D. Gerasimov, H. Javaherian, V. Nikiforov","doi":"10.1109/ACC.2011.5990626","DOIUrl":"https://doi.org/10.1109/ACC.2011.5990626","url":null,"abstract":"Effective control of spark ignition engines (SIE) under all operating conditions is essential for achieving high fuel economy, low emissions and high vehicle performance. Design and development of high performance control system is a challenging problem due to the variety of engine operating regimes, the complexity of nonlinear physical and chemical engine processes, a number of unmeasurable variables which directly affect important engine variables, multiplicity of control inputs and outputs, process/measurement noise and load disturbances. In this paper, the most important problems of torque tracking and air-to-fuel ratio (AFR) stabilization at the stoichiometric level are addressed. To provide a suitable solution for this problem, a data driven approach based on the design of direct and inverse models is proposed. The inverse model is represented by a grey box with a selected fixed structure, outputs which are the control variables and a set of input variables as nonlinear functions of the engine state and regulated variables. The direct model is also represented as a grey box, but the regulated variables are the model outputs and the control variables are the model inputs. The parameters of the grey box models are estimated through an offline identification procedure using vehicle data and a special representation of the models in the form of linear regressions. The controller is designed to maintain the combined gain of tandem \"inverse model direct model\" close to unity at all engine operating regimes. Two approaches for parameter estimation are proposed and justified. One approach is based on the substitution of the regulated desired value in the inverse model for its current value, and the other is based on the pseudo inverse of the direct model. Both approaches result in the design of a feedforward controller. In practice, the feedforward controller is augmented by a PID controller to provide improved performance in the presence of modeling errors and external disturbances. The final controller is robust to uncontrollable disturbances. Test results demonstrating the performance of the algorithms are presented and discussed.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114462091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of maximum-likelihood discrete-choice models of the runway configuration selection process","authors":"V. Ramanujam, H. Balakrishnan","doi":"10.1109/ACC.2011.5991446","DOIUrl":"https://doi.org/10.1109/ACC.2011.5991446","url":null,"abstract":"The runway configuration is the subset of the runways at an airport that are used for arrivals and departures at any time. Many factors, including weather (wind and visibility), expected arrival and departure demand, environmental considerations such as noise abatement procedures, and coordination of flows with neighboring airports, govern the choice of runway configuration. This paper develops a statistical model to characterize this process using empirical observations. In particular, we demonstrate how a maximum-likelihood discrete-choice model of the runway configuration process can be estimated using aggregate traffic count and other archived data at an airport, that are available over 15 minute intervals. We show that the estimated discrete-choice model not only identifies the influence of various factors in decision-making, but also provides significantly better predictions of runway configuration changes than a baseline model based on the frequency of occurrence of different configurations. The approach is illustrated using data from Newark (EWR) and LaGuardia (LGA) airports.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122061812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic optimal control of unknown linear networked control system using Q-learning methodology","authors":"Hao Xu, S. Jagannathan","doi":"10.1109/ACC.2011.5991278","DOIUrl":"https://doi.org/10.1109/ACC.2011.5991278","url":null,"abstract":"In this paper, the Bellman equation is utilized forward-in-time for the stochastic optimal control of Networked Control System (NCS) with unknown system dynamics in the presence of random delays and packet losses which are unknown. The proposed stochastic optimal control approach, referred normally as adaptive dynamic programming, uses an adaptive estimator (AE) and ideas from Q-learning to solve the infinite horizon optimal regulation control of NCS with unknown system dynamics. Update laws for tuning the unknown parameters of the adaptive estimator (AE) online to obtain the time-based Q-function are derived. Lyapunov theory is used to show that all signals are asymptotically stable (AS) and that the approximated control signals converge to optimal control inputs. Simulation results are included to show the effectiveness of the proposed scheme.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122064179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust SDC parameterization for a class of Extended Linearization systems","authors":"Sam Nazari, B. Shafai","doi":"10.1109/ACC.2011.5991555","DOIUrl":"https://doi.org/10.1109/ACC.2011.5991555","url":null,"abstract":"We consider nonlinear regulation of systems with parametric uncertainty. Under mild conditions, these systems can be brought into a psuedo-linear form known as extended linearization. Under this formulation, conventional linear control synthesis methods can be applied. One popular technique that mimics the LQR method of optimal linear control is referred to as the State-Dependent Riccati Equation (SDRE) approach. SDRE control relies on a non-unique factorization of the system dynamics known as the State Dependent Coefficient (SDC) parameterization. Under system uncertainty, each SDC parameterization will produce its own radius of stability in a region of interest in the state space. In this paper a method to compute the radius of stability in a special class of systems is used to obtain the SDC parameterization which results in the maximum radius of stability for the original nonlinear system in the region of interest. It is shown that the problem of finding the maximum radius of stability from a hyperplane of SDC parameterizations can be reduced to constrained minimization of the spectral norm of a comparison system.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117045752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive control of piecewise linear systems with applications to NASA GTM","authors":"Qian Sang, G. Tao","doi":"10.1109/ACC.2011.5990918","DOIUrl":"https://doi.org/10.1109/ACC.2011.5990918","url":null,"abstract":"Nonlinear plants with their operating range covering multiple trim points are modeled as piecewise linear systems, where variations in operating points are modeled as switches between constituent linearized system dynamics. The adaptive state feedback for state tracking control problem for such systems is studied, for which piecewise linear reference model systems are used to generate desired state trajectories. Adaptive control schemes are developed, and it is proved that asymptotic tracking performance can be achieved if the reference input is sufficiently rich and the switches are sufficiently slow. Stability and tracking performance of the proposed adaptive control schemes are analyzed and evaluated on the high-fidelity Simulink model of the Generic Transport Model (GTM) developed at NASA Langley.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128318550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust stability criteria for uncertain systems with delay and its derivative varying within intervals","authors":"L. F. C. Figueredo, J. Ishihara, G. Borges, A. Bauchspiess","doi":"10.1109/ACC.2011.5990910","DOIUrl":"https://doi.org/10.1109/ACC.2011.5990910","url":null,"abstract":"In this paper, stability criteria are proposed for linear systems liable to model uncertainties and with the delay and its derivative varying within intervals. The results are an improvement over previous ones due to the development of a new Lyapunov-Krasovskii functional (LKF). The analysis incorporates recent advances such as convex optimization technique and piecewise analysis method with new delay-interval depedent LKFs terms and a novel auxiliary delayed state. Stability conditions are provided for the cases when the delay derivative is upper and lower bounded, when the lower bound is unknown, and when no restrictions are cast upon the derivative. The analysis is enriched with numerical examples that illustrate the effectiveness of our criteria which outperform previous criteria in the literature for nominal and uncertain delayed systems.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128395171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}