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Impact of Driveability Constraints on Local Optimal Energy Management Strategies for Hybrid Powertrains

IFAC Proceedings Volumes 2013年第21期46卷 23-28页

作者： D. Bardini T. Leroy IFP Energies nouvelles 1&4 avenue de Bois Préau 92852 Rueil-Malmaison France

The paper deals with the issue of energy management in hybrid electric vehicles, considering possible solutions for addressing the power split in real-life conditions. The focus is on the comparison between two local optimal on-line energy management strategies: stochastic dynamic programming (SDP) and Equivalent Consumption Minimization Strategy (ECMS). First, results of fuel consumption for simulation on 100 random driving cycles for the two strategies, tuned for best fuel consumption, are provided. Then, some driveability considerations, regarding engine utilization profile and dwell time, are made. The results of the simulation of the two strategies incorporating driveability constraints are discussed, showing a substantial change of situation with respect to the initial case.

关键词： Driveability Energy Management Equivalent Consumption Minimization Strategy Pontryagin's Minimum Principle stochastic dynamic programming

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A stochastic Security Game for Kalman Filtering in Networked Control Systems (NCSs) under Denial of Service (DoS) Attacks

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IFAC Proceedings Volumes 2013年第20期46卷 106-111页

作者： Shichao Liu P. Xiaoping Liu Abdulmotaleb El Saddik Department of Systems and Computer Engineering Carleton University Ottawa ON K1S 5B6 Canada School of Information Technology and Engineering University of Ottawa Ottawa ON K1N 6N5 Canada

In this paper, we investigate the problem how to design optimal security mechanism for the Kalman filtering of Networked Control Systems (NCSs) with a DoS attacker under limited resources. A two-player zero-sum stochastic game is formulated to model not only the dynamic interaction between the network administrator (as a defender) and the DoS attacker (as an attacker), but also the transitions between the two states (on/off) of the communication link. In specific, we take the degraded dynamic performance of physical systems into consideration when we design the network security mechanism. In this stochastic game, the cost function consists of two parts: one component is the network resource cost, the other one is the degraded dynamic performance of the Kalman filtering of the NCS, indexing by the trace of the estimation error covariance matrix. The optimal defense and attack strategies are obtained by using stochastic dynamic programming (SDP). A linear NCS is used to illustrate the procedure of the proposed stochastic game formulation and solving it by SDP.

关键词： Networked control systems denial-of-service (DoS) attacks stochastic game stochastic dynamic programming Kalman Filter

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Analytical modelling and control of a hybrid manufacturing/remanufacturing system

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IFAC Proceedings Volumes 2013年第9期46卷 401-406页

作者： Annie Francie Kouedeu Jean-Pierre Kenne Pierre Dejax Victor Songmene Vladimir Polotski Mechanical Engineering Department Laboratory of Integrated Production Technologies University of Quebec École de Technologie Supérieure 1100 Notre Dame Street West Montreal (Quebec) Canada H3C 1K3 LUNAM École des Mines de Nantes IRCCyN La Chantrerie 4 Rue Alfred Kastler PO Box 20722 - 44307 Nantes Cedex 3 - France

A production system consisting of parallel machines deteriorating with the production dependent failure rates of the machine is investigated in this paper and extended within the framework of a manufacturing/remanufacturing system within a closed loop reverse logistics system The machines produce one type of final products. The demand rate for the final commodity is constant and unmet demand is backlogged. The goal is to find the production rates of both machines so as to minimize a long term average expected cost which includes backlogging as well as inventory costs. In the proposed model, the main machine (characterized by a higher production rate) is more robust than the second machine. The failure rate of the main machine depends on its production rate, while the failure rate of the second machine is constant. This paper proposes a stochastic dynamic programming formulation of the problem and derives the optimal production policies numerically. A simulation example is included, and sensitivity analyses with respect to the system parameters are examined to illustrate the effectiveness of the proposed methodology.

关键词： Production planning Remanufacturing stochastic dynamic programming Numerical methods Reverse logistics

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KALMAN-LIKE STATE TRACKING AND CONTROL IN POMDPS WITH APPLICATIONS TO BODY SENSING NETWORKS

KALMAN-LIKE STATE TRACKING AND CONTROL IN POMDPS WITH APPLIC...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Daphney-Stavroula Zois Marco Levorato Urbashi Mitra Ming Hsieh Department of Electrical Enginering University of Southern California

ISBN: (纸本)9781479903573

In this paper, the problem of state tracking with controlled observations is considered for a system modeled by a discrete-time, finite-state Markov chain. The system state is 'hidden' and observed via conditionally Gaussian measurements that are shaped by the underlying state and an exogenous control input. Following an innovations approach, a Kalman-like filter is derived to estimate the Markov chain system state. To optimize the control strategy, the associated mean-squared error is used as an optimization criterion for a partially observable Markov Decision Process (POMDP). The optimal solution is determined via stochastic dynamic programming. Numerical results are presented for the application of physical activity detection in heterogeneous, wireless body area networks.

关键词： Markov models Approximate MMSE POMDP stochastic dynamic programming Innovations approach

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Optimal operation of hydrothermal systems with Hydrological Scenario Generation through Bootstrap and Periodic Autoregressive Models

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2012年第3期222卷 606-615页

作者： Souza, Reinaldo Castro Marques Marcato, Andre Luis Dias, Bruno Henriques Cyrino Oliveira, Fernando Luiz Univ Fed Juiz de Fora Juiz De Fora Brazil Pontifical Catholic Univ Rio de Janeiro Rio De Janeiro Brazil Univ Fed Fluminense Niteroi RJ Brazil

In electrical power systems with strong hydro generation, the use of adequate techniques to generate synthetic hydrological scenarios is extremely important for the evaluation of the ways the system behaves in order to meet the forecast energy demand. This paper proposes a new model to generate natural inflow energy scenarios in the long-term operation planning of large-sized hydrothermal systems. This model is based on the Periodic Autoregressive Model, PAR (p), where the identification of the p orders is based on the significance of the Partial Autocorrelation Function (PACF) estimated via Bootstrap, an intensive computational technique. The scenarios generated through this new technique were applied to the operation planning of the Brazilian Electrical System (BES), using the previously developed methodology of stochastic dynamic programming based on Convex Hull algorithm (SDP-CHull). The results show that identification via Bootstrap is considerably more parsimonious, leading to the identification of lower orders models in most cases which retains the statistical characteristics of the original series. Additionally it presents a closer total mean operation cost when compared to the cost obtained via historic series. (C) 2012 Elsevier B.V. All rights reserved.

关键词： OR in energy Long-term operation planning Periodic model Bootstrap stochastic dynamic programming

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Optimization of Perimeter Patrol Operations Using Unmanned Aerial Vehicles

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JOURNAL OF GUIDANCE CONTROL AND dynamicS 2012年第2期35卷 434-441页

作者： Kalyanam, Krishnamoorthy Chandler, Phil Pachter, Meir Darbha, Swaroop Infoscitex Corp Dayton OH 45431 USA USAF Res Lab Control Design & Anal Branch Wright Patterson AFB OH 45433 USA USAF Inst Technol Dept Elect Engn Wright Patterson AFB OH 45433 USA Texas A&M Univ Dept Mech Engn College Stn TX 77843 USA

This paper addresseses the following base perimeter patrol problem: a team of unmanned aerial vehicles (UAVs) equipped with cameras and a remotely located operator cooperatively perform the task of perimeter surveillance. There are m alert stations/sites on the perimeter where a nearby breaching of the perimeter by an intruder is flagged by an unattended ground sensor (UGS). To determine whether an incursion flagged by a UGS is a false alarm or a real threat, a patrolling UAV flies to the alert site to investigate the alert. The longer a UAV dwells (loiters) at an alert site, the more information it gathers;however, this also increases the delay in responding to other alerts. The decision problem for a UAV is to determine the optimal dwell time so as to maximize the expected payoff. In this paper, patrols consisting of one and two UAVs are considered. A stochastic dynamic programming approach is employed to obtain optimal policies for the patrolling UAVs. Theoretical performance bounds from queueing systems literature have been used to benchmark the optimal controller. Also, simulation results for the optimal patrols showing the expected information gained and response time for different alert arrival rates are presented.

关键词： UAV stochastic dynamic programming Sensors Markov Decision Process Monte Carlo Simulation Probability Density Functions MATLAB

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A fuzzy-Markov-chain-based analysis method for reservoir operation

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stochastic ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2012年第3期26卷 375-391页

作者： Fu, D. Z. Li, Y. P. Huang, G. H. N China Elect Power Univ MOE Key Lab Reg Energy Syst Optimizat SC Energy & Environm Res Acad Beijing 102206 Peoples R China

In this study, a fuzzy-Markov-chain-based stochastic dynamic programming (FM-SDP) method is developed for tackling uncertainties expressed as fuzzy sets and distributions with fuzzy probability (DFPs) in reservoir operation. The concept of DFPs used in Markov chain is presented as an extended form for expressing uncertainties including both stochastic and fuzzy characteristics. A fuzzy dominance index analysis approach is proposed for solving multiple fuzzy sets and DPFs in the proposed FM-SDP model. Solutions under a set of alpha-cut levels and fuzzy dominance indices can be generated by solving a series of deterministic submodels. The developed method is applied to a case study of a reservoir operation system. Solutions from FM-SDP provide a range of desired water-release policies under various system conditions for reservoir operation decision makers, reflecting dynamic and dual uncertain features of water availability simultaneously. The results indicate that the FM-SDP method could be applicable to practical problems for decision makers to obtain insight regarding the tradeoffs between economic and system reliability criteria. Willingness to obtain a lower benefit may guarantee meeting system-constraint demands;conversely, a desire to acquire a higher benefit could run into a higher risk of violating system constraints.

关键词： Decision making Dual uncertainties Fuzzy Markov chain stochastic dynamic programming Reservoir operation

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Partial Equilibrium in Risk-Based Production Decisions

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NAVAL RESEARCH LOGISTICS 2012年第1期59卷 1-17页

作者： Kamrad, Bardia Siddique, Akhtar Ernst, Ricardo Georgetown Univ McDonough Sch Business Washington DC 20057 USA Off Comptroller Currency Enterprise Risk Anal Div Washington DC 20219 USA

Characteristically, a small subset of operational problems admit risk neutrality when contingent claims methodology were used in their analysis. That is, for the majority of manufacturing and production problems, operating cash flows are not directly linked to prices of traded assets. However, to the extent that correlations can be estimated, the methodology's applicability to a broader set of operational problems is supported. Our article addresses this issue with the objective of extending the use of contingent claims techniques to a larger set of operational problems. In broad terms, this objective entails a partial equilibrium approach to the problem of valuing uncertain cash flows. To this end, we assume risk aversion and cast our approach within Merton's intertemporal capital asset pricing model. In this context, we formulate a "generic" production valuation model that is framed as an exercise in stochastic optimal control. The model is versatile in its characterization and can easily be adapted to accommodate a wide-ranging set of risk-based operational problems where the underlying sources of uncertainty are not traded. To obtain results, the model is recast as a stochastic dynamic program to be solved numerically. The article addresses a number of fundamental issues in the analysis risk based decision problems in operations. First, in the approach provided, decisions are analyzed under a properly defined risk structure. Second, the process of analysis leads to suitably adjusted probability distributions through which, appropriately discounted expectations are derived. Third, through consolidating existing concepts into a standard and adaptable framework, we extend the applicability of contingent claims methodology to a broader set of operational problems. The approach is advantageous as it obviates the need for exogenously specifying utility functions or discount rates. (C) 2011 Wiley Periodicals, Inc. Naval Research Logistics 59: 1-17, 2012

关键词： contingent claims analysis in production operations control theory Merton's intertemporal capital asset pricing model stochastic dynamic programming risk management in operations

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Control of a production-inventory system with returns under imperfect advance return information

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2012年第2期218卷 392-400页

作者： Flapper, S. D. P. Gayon, J. P. Vercraene, S. Grenoble Inst Technol Lab G SCOP F-38031 Grenoble France Tech Univ Eindhoven NL-5600 MB Eindhoven Netherlands

We consider a production-inventory system with product returns that are announced in advance by the customers. Demands and announcements of returns occur according to independent Poisson processes. An announced return is either actually returned or cancelled after a random return lead time. We consider both lost sale and backorder situations. Using a Markov decision formulation, the optimal production policy, with respect to the discounted cost over an infinite horizon, is characterized for situations with and without advance return information. We give insights in the potential value of this information. Also some attention is paid to combining advance return and advance demand information. Further applications of the model as well as topics for further research are indicated. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Reverse logistics Inventory control stochastic dynamic programming Advance return information

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Production planning of a hybrid manufacturing-remanufacturing system under uncertainty within a closed-loop supply chain

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2012年第1期135卷 81-93页

作者： Kenne, Jean-Pierre Dejax, Pierre Gharbi, Ali IRCCyN Ecole Mines Nantes Logist & Prod Syst Grp Dept Automat Control & Ind Engn F-44307 Nantes 3 France Univ Quebec Dept Mech Engn Lab Integrated Prod Technol Ecole Technol Super Montreal PQ H3C 1K3 Canada Univ Quebec Automated Prod Engn Dept Prod Syst Design & Control Lab Ecole Technol Super Montreal PQ H3C 1K3 Canada

This paper deals with the production planning and control of a single product involving combined manufacturing and remanufacturing operations within a closed-loop reverse logistics network with machines subject to random failures and repairs. While consumers traditionally dispose of products at the end of their life cycle, recovery of the used products may be economically more attractive than disposal, while remanufacturing of the products also pursues sustainable development goals. Three types of inventories are involved in this network. The manufactured and remanufactured items are stored in the first and second inventories. The returned products are collected in the third inventory and then remanufactured or disposed of. The objective of this research is to propose a manufacturing/remanufacturing policy that would minimize the sum of the holding and backlog costs for manufacturing and remanufacturing products. The decision variables are the production rates of the manufacturing and the remanufacturing machines. The optimality conditions are developed using the optimal control theory based on stochastic dynamic programming. A computational algorithm, based on numerical methods, is used for solving the optimal control problem. Finally, a numerical example and a sensitivity analysis are presented to illustrate the usefulness of the proposed approach. The structure of the optimal control policy is discussed depending on the value of costs and parameters and extensions to more complex reverse logistics networks are discussed. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Reverse logistics Closed-loop supply chains Manufacturing/remanufacturing Optimal control Production planning stochastic dynamic programming Numerical methods

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