{"title":"Optimizing Online Control of Constrained Systems with Switched Dynamics","authors":"Zonglin Liu, O. Stursberg","doi":"10.23919/ECC.2018.8550446","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550446","url":null,"abstract":"This paper studies the online control of switched systems over a finite time horizon subject to time-varying constraints on the continuous states and bounded input set. The formulation leads to optimization problems of the class mixedinteger nonlinear programming (MINLP), which is known to be computationally hard. This paper proposes a method to approximate the optimal solution while keeping the computational effort low enough, to enable real-time applicability for many systems. The main idea is to use heuristics based on the value function for relaxed sub-problems to prune the tree encoding the possible sequences of discrete choices (i.e. the selected continuous dynamics) over a prediction horizon. Numeric tests show that the times for computation are drastically below those for standard MINLP solution in the vast majority of cases, while good approximations of the optimal solutions are obtained.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"108 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125189636","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":"System Identification and Indirect Inverse Control Using Fuzzy Cognitive Networks with Functional Weights","authors":"Georgios D. Karatzinis, Y. Boutalis, T. Kottas","doi":"10.23919/ECC.2018.8550376","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550376","url":null,"abstract":"A Fuzzy Cognitive Network (FCN) is an operational extension of a Fuzzy Cognitive Map (FCM) which assumes, first, that it always converges to equilibrium points during its operation and second, it is in continuous interaction with the system it describes and may be used to control it. In this paper we show that the conditions that guarantee the convergence of the FCN may lead to a special, yet very powerful, form of the network that assumes functional interconnection weights with excellent system approximation abilities. Assuming that the plant is unknown it is initially approximated by a FCN and a procedure for adaptive estimation of its functional weights is proposed that guarantee approximation error convergence to zero. The FCN is then used for the Indirect adaptive Inverse Control of a plant. The methodology is tested on a coupled two-tank system.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131283042","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":"A Network Reduction Method Inducing Scale-Free Degree Distribution","authors":"Nicolas Martin, P. Frasca, C. Canudas-de-Wit","doi":"10.23919/ECC.2018.8550581","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550581","url":null,"abstract":"This paper deals with the problem of graph reduction towards a scale-free graph while preserving a consistency with the initial graph. This problem is formulated as a minimization problem and to this end we define a metric to measure the scale-freeness of a graph and another metric to measure the similarity between two graphs with different dimensions, based on spectral centrality. We also want to ensure that if the initial network is a flow network, the reduced network preserves this property. We explore the optimization problem and, based on the gained insights, we derive an algorithm allowing to find an approximate solution. Finally, the effectiveness of the algorithm is shown through a simulation on a Manhattan-like network.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131410116","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":"Minimizing Regret in Unconstrained Online Convex Optimization","authors":"T. Tatarenko, M. Kamgarpour","doi":"10.23919/ECC.2018.8550310","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550310","url":null,"abstract":"We consider online convex optimizations in the bandit setting. The decision maker does not know the time- varying cost functions, or their gradients. At each time step, she observes the value of the cost function for her chosen action. The objective is to minimize the regret, that is, the difference between the sum of the costs she accumulates and that of the optimal action computable had she known the cost functions a priori. We present a novel algorithm in order to minimize the regret in an unconstrained action space. Our algorithm hinges on the idea of introducing randomization to approximate the gradients of the cost functions using only their observed values. We establish an almost sure regret bound for the mean values of actions and an expected regret bound for the actions.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"52 24","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131472450","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":"Distributed Best Response Algorithms for Potential Games","authors":"Stéphane Durand, Federica Garin, B. Gaujal","doi":"10.23919/ECC.2018.8550412","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550412","url":null,"abstract":"In this paper we design and analyze distributed algorithms to compute a Nash equilibrium in potential games. Our algorithms are based on best-response dynamics, with suitable revision sequences (orders of play). We compute the average complexity over all potential games of best response dynamics under a random i.i. d. revision sequence, since it can be implemented in a distributed way using Poisson clocks. We obtain a distributed algorithm whose execution time is within a constant factor of the optimal centralized one.We then show how to take advantage of the structure of the interactions between players in a network game: non-interacting players can play simultaneously. This improves best response algorithm, both in the centralized and in the distributed case.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131644391","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":"Implementation of Model Predictive Controllers in Programmable Logic Controllers using IEC 61131-3 standard","authors":"Pablo Krupa, D. Limón, T. Alamo","doi":"10.23919/ECC.2018.8550126","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550126","url":null,"abstract":"This work presents a tool for implementing Model Predictive Controllers (MPC) in Programmable Logic Controllers (PLC). This tool is a Matlab library that automatically generates the controller’s code using IEC 61131-3 standards so that it can be directly imported into the PLC’s programming platform as an FBD block, which is designed to work using the cyclic mode of the PLC and has a limited maximum execution time. A hand-tailored optimization algorithm based on a fast gradient method named FISTA has been developed in order to reduce the necessary memory and computational resources. A complete architecture has been designed surrounding the MPC which provides the overall controller with a series of additional capabilities. The properties of the controller have been validated via a test-bed using a Modicom M340 PLC to control a quadruple-tank system. In addition, tests have been conducted in order to study the memory requirements.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115159238","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":"Set-Induced Anomaly Detectors for Networked Power Systems under Bias Injection Cyber-Attacks","authors":"E. Kontouras, A. Tzes, L. Dritsas","doi":"10.23919/ECC.2018.8550393","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550393","url":null,"abstract":"This paper addresses the concept of a set-induced anomaly detector of bias injection cyber-attacks affecting the load frequency control loop of a networked power system. An adversary corrupts the frequency sensor measurements causing abnormal system behavior. A set-theoretic methodology is used for the extraction of a convex and compact polyhedral robust invariant set under the overall discretized network dynamics. An attack is considered disclosed when the state vector exits the invariant set. Simulation studies demonstrate the impact of an intermittent attack on a two-area power plant and provide an assessment of the proposed detector, when the attack happens simultaneously with changes in the power load demand.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"72 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128015163","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}
A. Anderson, A. González, A. Ferramosca, E. Kofman
{"title":"Finite-time convergence results in Model Predictive Control","authors":"A. Anderson, A. González, A. Ferramosca, E. Kofman","doi":"10.23919/ECC.2018.8550143","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550143","url":null,"abstract":"Asymptotic stability (convergence and $epsilon-delta$ stability) of invariant sets under model predictive control (MPC) strategies have been extensively studied in the last decades. Lyapunov theory is in some sense the common denominator of the different forms to achieve such results. However, the meaningful problem of the finite-time convergence (for a given fixed control horizon) has not received much attention in the literature (with some remarkable exceptions). In this work a novel set-based MPC that ensures finite-time convergence in a natural way is presented. The contractivity and non-empty interior conditions of the target set, the consideration of an appropriate input set and the continuity of the dynamic model are the main hypothesis to be made. An upper bound for the convergence time is also provided.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133462495","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":"Development of a Control Theoretic Based Simulation Model of a Supply and Distribution System with Reusable Items","authors":"O. Rehman, M. Ryan","doi":"10.23919/ECC.2018.8550292","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550292","url":null,"abstract":"Control theoretic modelling and control approaches provide a systematic way to address the problem associated with inventory control of supply and distribution systems. Supply chain systems usually contain a number of lead times among supply nodes and are susceptible to demand variation. In this work, we developed a linear uncertain discrete time model of a distribution system with multiple supply nodes and pure delays by considering reusable supply items and multiple supply chains. The model allows for a three-level distribution system which include customer, distributor and plant, where customers can also supply items to other requesting customers. The model presented here paves the way towards developing robust control policies for distribution of items under state and input constraints. In order to determine robust resources a discrete event simulation model is developed based on the proposed discrete model using Simulink® toolbox SimEvents. Finally a robust distribution policy and item return policy is obtained considering operational cost and customer satisfaction.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133499439","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":"Wind Farm Power Forecasting for Less Than an Hour Using Multi Dimensional Models","authors":"T. Knudsen, T. Bak, T. Jensen","doi":"10.23919/ECC.2018.8550286","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550286","url":null,"abstract":"This research focuses on prediction of wind farm power for horizons of 0–10 minutes and not more than one hour using statistical methods. These short term predictions are relevant for both transmission system operators, wind farm operators and traders. Previous research indicates that for short time horizons the persistence method performs as well as more complex methods. However, these results are based on accumulated power for an entire wind farm. The contribution in this paper is to develop multi-dimensional linear methods based on measurements of power or wind speed from individual wind turbine in a wind farm. These multi-dimensional methods are compared with the persistence method using real 1 minute average data from the Sheringham Shoal wind farm with 88 turbines. The results show that the use of measurements from individual turbines reduce the prediction errors 5–10% and also improves the prediction error variance estimate compared to the persistence method. We also present convincing examples showing that the predictions follow the wind farm power over a window of an hour.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133720062","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}