Application of Machine Learning to Performance Assessment for a class of PID-based Control Systems

In this paper, a novel machine learning derived control performance assesment (CPA) classification system is proposed. It is dedicated for a class of PID-based control loops with processes exhibiting second order plus delay time (SOPDT) dynamical properties. The proposed concept is based on deriving and combining a number of different, diverse control performance indices (CPIs) that separately do not provide sufficient information about the control performance. However, when combined together and used as discriminative features of the assessed control system, they can provide consistent and accurate CPA information. This concept is discussed in terms of the introduced extended set of CPIs, comprehensive performance assessment of different machine learning based classification methods and practical applicability of the suggested solution. The latter is shown and verified by practical application of the proposed approach to a CPA system for a laboratory heat exchange and ditribution setup.Comment: Submitted to IEEE Transactions on Industrial Electronic

Measurements, Models, Systems and Design

531 s.

Journal of Telecommunications and Information Technology, 2019, nr 2

kwartalni

Engineering Dynamics and Life Sciences

From Preface: This is the fourteenth time when the conference “Dynamical Systems: Theory and Applications” gathers a numerous group of outstanding scientists and engineers, who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without a great effort of the staff of the Department of Automation, Biomechanics and Mechatronics. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and Ministry of Science and Higher Education of Poland. It is a great pleasure that our invitation has been accepted by recording in the history of our conference number of people, including good colleagues and friends as well as a large group of researchers and scientists, who decided to participate in the conference for the first time. With proud and satisfaction we welcomed over 180 persons from 31 countries all over the world. They decided to share the results of their research and many years experiences in a discipline of dynamical systems by submitting many very interesting papers. This year, the DSTA Conference Proceedings were split into three volumes entitled “Dynamical Systems” with respective subtitles: Vibration, Control and Stability of Dynamical Systems; Mathematical and Numerical Aspects of Dynamical System Analysis and Engineering Dynamics and Life Sciences. Additionally, there will be also published two volumes of Springer Proceedings in Mathematics and Statistics entitled “Dynamical Systems in Theoretical Perspective” and “Dynamical Systems in Applications”

Robust Regulation for Infinite-Dimensional Systems and Signals in the Frequency Domain

In this thesis, the robust output regulation problem is studied both in the time domain and in the frequency domain. The problem to be addressed is to find a stabilizing controller for a given plant so that every signal generated by an exogenous system, or shortly exosystem, is asymptotically tracked despite perturbations in the plant or some external disturbances. The exosystem generating the reference and disturbance signals is assumed to be infinite-dimensional. The main contribution of this thesis is to develop the robust regulation theory for an infinite-dimensional exosystem in the frequency domain framework. In order to do that, the time domain theory is studied in some detail and new results that emphasize the smoothness requirement on the reference and disturbance signals due to infinite-dimensionality of the exosystem are presented. Two types of controllers are studied, the feedforward controllers and the error feedback controllers, the latter of which facilitate robust regulation. These results exploit the structure at infinity of tha plant transfer function. In this thesis, a new definition of the structure at infinity suitable for infinite-dimensional systems is developed and its properties are studied. The frequency domain theory developed is based on the insights into the corresponding time domain theory. By following some recent time domain ideas the type of robustness and stability types are chosen so that they facilitate the use of an infinite-dimensional exosystem. The robustness is understood in the sense that stability should imply regulation. The chosen stability types resemble the time domain polynomial and strong stabilities and allow robust regulation of signals that have an infinite number of unstable dynamics along with transfer functions vanishing at infinity. The main contribution of this thesis is the formulation of the celebrated internal model principle in the frequency domain terms in a rather abstract algebraic setting. Unlike in the existing literature, no topological aspect of the problem is needed because of the adopted definition of robustness. The plant transfer function is only assumed to have a right or a left coprime factorization but not necessarily both. The internal model principle leads to a necessary and sufficient condition for the solvability of the robust regulation problem. The second main contribution of the thesis is to design frequency domain controllers for infinite-dimensional systems and exosystems. In this thesis, the Davison’s simple controller design for stable plants is extended to infinite-dimensional systems and exosystems. Then a controller design procedure for unstable plants containing two phases is proposed. In the first phase, a stabilizing controller is constructed for a given plant. The second phase is to design a robustly regulating controller for a stable part of the plant. This design procedure nicely combines with the Davison’s type controllers and is especially suitable for infinite-dimensional plants with transfer functions in the Callier-Desoer class of transfer functions

Optimalizacija sustava s diskretnim događajima primjenom Petrijevih mreža i genetskih algoritama

Rad obrađuje pretpostavke za izgradnju i primjenu općenitog modela, koji integrira Petrijeve mreže i genetske algoritme s ciljem kontinuiranog nadzora poslova u sustavu s diskretnim događajima (DES) i usmjeravanja sustava u željenom smjeru. U prvoj fazi detaljno je opisana metoda simulacije DES-a pomoću općih Petrijevih mreža (PM). U nastavku predstavljene su osnove određivanja rasporeda poslova, metode evolucijskog računanja, s posebnim naglaskom na genetskih algoritam (GA). U drugoj fazi pristupilo se izradi modela i algoritma uvođenjem matričnog modela MRF1 klase PM i GA, s ciljem određivanja rasporeda poslova u više-projektnom sustavu s višeradnim resursima ograničenog kapaciteta pomoću heurističkih pravila, u kojem su prioriteti, kašnjenja i raspoloživost poslova definirani kroz genetski algoritam. U trećoj fazi algoritam je verificiran na dva sustava. Prvi sustav je pomorski prometni sustav kanala u kojem može nastupiti stanje potpunog zastoja neodgovarajućim zauzimanjem kanala od strane brodova koji prolaze suprotnim smjerovima. Drugi sustav je kontejnerski terminal. Razmatra se problem rasporeda poslova za automatski upravljana vozila. Cilj je izbjeći konflikte i zastoje među vozilima te minimalizirati vrijeme čekanja na dizalice, uz što kraća zadržavanja broda u luci. Algoritam je vrednovan s različitim veličinama populacije kako bi ispitao utjecaj tog parametra na konvergenciju rezultata ka konačnom rješenju. Rezultati primjene predloženog algoritma, kao i matrične metode nadzornika za sprječavanje zastoja, ukazuju na njegovu učinkovitost i robusnost.This paper deals with assumptions for creation and implementation of the universal model for integration Petri nets and genetic algorithms, whose primary goal is to constantly control all jobs in a discrete event system and to guide the system to the targeted destination. In the first phase, the method of simulation discrete event system using Petri nets (PN) was described. Hereafter the basis for determining work schedules, methods of evolutionary computation, with special emphasis on genetic algorithm were presented. The aim of the second phases was to construct the integration method of genetic algorithm (GA) and matrix models MRF1 Petri nets into a comprehensive system of assigning jobs. It is necessary to determine the job schedule in a multi-project system with shared resources using heuristic rules which are priorities, delays and availability of jobs defined by genetic algorithm. The emphasis of the third phase was the verification of proposed algorithm at two systems. The first system is maritime traffic canal system in which to complete deadlock can be reached by taking improper channels by ships passing in opposite directions. The second system is a container terminal. We consider the problem of distribution jobs for unmanned vehicles to transport containers within the terminal. To increase the efficiency of container terminals, the proposed algorithm involves the procedure for forecasting and avoiding the conflicts and deadlocks. Also, the algorithm minimizes the waiting time for resources and minimizes the time that a ship spends in port. The algorithm was evaluated with different population sizes to examine the influence of this parameter on the convergence of results towards the final solution. The test results show the effectiveness and robustness of the proposed integration of GA and PN to determine the job schedule in a discrete event system

Optimalizacija sustava s diskretnim događajima primjenom Petrijevih mreža i genetskih algoritama

Rad obrađuje pretpostavke za izgradnju i primjenu općenitog modela, koji integrira Petrijeve mreže i genetske algoritme s ciljem kontinuiranog nadzora poslova u sustavu s diskretnim događajima (DES) i usmjeravanja sustava u željenom smjeru. U prvoj fazi detaljno je opisana metoda simulacije DES-a pomoću općih Petrijevih mreža (PM). U nastavku predstavljene su osnove određivanja rasporeda poslova, metode evolucijskog računanja, s posebnim naglaskom na genetskih algoritam (GA). U drugoj fazi pristupilo se izradi modela i algoritma uvođenjem matričnog modela MRF1 klase PM i GA, s ciljem određivanja rasporeda poslova u više-projektnom sustavu s višeradnim resursima ograničenog kapaciteta pomoću heurističkih pravila, u kojem su prioriteti, kašnjenja i raspoloživost poslova definirani kroz genetski algoritam. U trećoj fazi algoritam je verificiran na dva sustava. Prvi sustav je pomorski prometni sustav kanala u kojem može nastupiti stanje potpunog zastoja neodgovarajućim zauzimanjem kanala od strane brodova koji prolaze suprotnim smjerovima. Drugi sustav je kontejnerski terminal. Razmatra se problem rasporeda poslova za automatski upravljana vozila. Cilj je izbjeći konflikte i zastoje među vozilima te minimalizirati vrijeme čekanja na dizalice, uz što kraća zadržavanja broda u luci. Algoritam je vrednovan s različitim veličinama populacije kako bi ispitao utjecaj tog parametra na konvergenciju rezultata ka konačnom rješenju. Rezultati primjene predloženog algoritma, kao i matrične metode nadzornika za sprječavanje zastoja, ukazuju na njegovu učinkovitost i robusnost.This paper deals with assumptions for creation and implementation of the universal model for integration Petri nets and genetic algorithms, whose primary goal is to constantly control all jobs in a discrete event system and to guide the system to the targeted destination. In the first phase, the method of simulation discrete event system using Petri nets (PN) was described. Hereafter the basis for determining work schedules, methods of evolutionary computation, with special emphasis on genetic algorithm were presented. The aim of the second phases was to construct the integration method of genetic algorithm (GA) and matrix models MRF1 Petri nets into a comprehensive system of assigning jobs. It is necessary to determine the job schedule in a multi-project system with shared resources using heuristic rules which are priorities, delays and availability of jobs defined by genetic algorithm. The emphasis of the third phase was the verification of proposed algorithm at two systems. The first system is maritime traffic canal system in which to complete deadlock can be reached by taking improper channels by ships passing in opposite directions. The second system is a container terminal. We consider the problem of distribution jobs for unmanned vehicles to transport containers within the terminal. To increase the efficiency of container terminals, the proposed algorithm involves the procedure for forecasting and avoiding the conflicts and deadlocks. Also, the algorithm minimizes the waiting time for resources and minimizes the time that a ship spends in port. The algorithm was evaluated with different population sizes to examine the influence of this parameter on the convergence of results towards the final solution. The test results show the effectiveness and robustness of the proposed integration of GA and PN to determine the job schedule in a discrete event system

Optimalizacija sustava s diskretnim događajima primjenom Petrijevih mreža i genetskih algoritama

Rad obrađuje pretpostavke za izgradnju i primjenu općenitog modela, koji integrira Petrijeve mreže i genetske algoritme s ciljem kontinuiranog nadzora poslova u sustavu s diskretnim događajima (DES) i usmjeravanja sustava u željenom smjeru. U prvoj fazi detaljno je opisana metoda simulacije DES-a pomoću općih Petrijevih mreža (PM). U nastavku predstavljene su osnove određivanja rasporeda poslova, metode evolucijskog računanja, s posebnim naglaskom na genetskih algoritam (GA). U drugoj fazi pristupilo se izradi modela i algoritma uvođenjem matričnog modela MRF1 klase PM i GA, s ciljem određivanja rasporeda poslova u više-projektnom sustavu s višeradnim resursima ograničenog kapaciteta pomoću heurističkih pravila, u kojem su prioriteti, kašnjenja i raspoloživost poslova definirani kroz genetski algoritam. U trećoj fazi algoritam je verificiran na dva sustava. Prvi sustav je pomorski prometni sustav kanala u kojem može nastupiti stanje potpunog zastoja neodgovarajućim zauzimanjem kanala od strane brodova koji prolaze suprotnim smjerovima. Drugi sustav je kontejnerski terminal. Razmatra se problem rasporeda poslova za automatski upravljana vozila. Cilj je izbjeći konflikte i zastoje među vozilima te minimalizirati vrijeme čekanja na dizalice, uz što kraća zadržavanja broda u luci. Algoritam je vrednovan s različitim veličinama populacije kako bi ispitao utjecaj tog parametra na konvergenciju rezultata ka konačnom rješenju. Rezultati primjene predloženog algoritma, kao i matrične metode nadzornika za sprječavanje zastoja, ukazuju na njegovu učinkovitost i robusnost.This paper deals with assumptions for creation and implementation of the universal model for integration Petri nets and genetic algorithms, whose primary goal is to constantly control all jobs in a discrete event system and to guide the system to the targeted destination. In the first phase, the method of simulation discrete event system using Petri nets (PN) was described. Hereafter the basis for determining work schedules, methods of evolutionary computation, with special emphasis on genetic algorithm were presented. The aim of the second phases was to construct the integration method of genetic algorithm (GA) and matrix models MRF1 Petri nets into a comprehensive system of assigning jobs. It is necessary to determine the job schedule in a multi-project system with shared resources using heuristic rules which are priorities, delays and availability of jobs defined by genetic algorithm. The emphasis of the third phase was the verification of proposed algorithm at two systems. The first system is maritime traffic canal system in which to complete deadlock can be reached by taking improper channels by ships passing in opposite directions. The second system is a container terminal. We consider the problem of distribution jobs for unmanned vehicles to transport containers within the terminal. To increase the efficiency of container terminals, the proposed algorithm involves the procedure for forecasting and avoiding the conflicts and deadlocks. Also, the algorithm minimizes the waiting time for resources and minimizes the time that a ship spends in port. The algorithm was evaluated with different population sizes to examine the influence of this parameter on the convergence of results towards the final solution. The test results show the effectiveness and robustness of the proposed integration of GA and PN to determine the job schedule in a discrete event system