A non-uniform predictor-observer for a networked control system

The final publication is available at Springer via http://dx.doi.org/10.1007/s12555-011-0621-5This paper presents a Non-Uniform Predictor-Observer (NUPO) based control approach in order to deal with two of the main problems related to Networked Control Systems (NCS) or Sensor Networks (SN): time-varying delays and packet loss. In addition, if these delays are longer than the sampling period, the packet disordering phenomenon can appear. Due to these issues, a (scarce) nonuniform, delayed measurement signal could be received by the controller. But including the NUPO proposal in the control system, the delay will be compensated by the prediction stage, and the nonavailable data will be reconstructed by the observer stage. So, a delay-free, uniformly sampled controller design can be adopted. To ensure stability, the predictor must satisfy a feasibility problem based on a time-varying delay-dependent condition expressed in terms of Linear Matrix Inequalities (LMI). Some aspects like the relation between network delay and robustness/performance trade-off are empirically studied. A simulation example shows the benefits (robustness and control performance improvement) of the NUPO approach by comparison to another similar proposal. © ICROS, KIEE and Springer 2011.This work was supported by the Spanish Ministerio de Ciencia y Tecnologia Projects DPI2008-06737-C02-01 and DPI2009-14744-C03-03, by Generalitat Valenciana Project GV/2010/018, by Universidad Politecnica de Valencia Project PAID06-08.Cuenca Lacruz, ÁM.; García Gil, PJ.; Albertos Pérez, P.; Salt Llobregat, JJ. (2011). A non-uniform predictor-observer for a networked control system. International Journal of Control, Automation and Systems. 9(6):1194-1202. doi:10.1007/s12555-011-0621-5S1194120296K. Ogata, Discrete-time Control Systems, Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1987.Y. Tipsuwan and M. Chow, “Control methodologies in networked control systems,” Control Eng. 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Piza, “A delay-dependent dual-rate PID controller over an Ethernet network,” IEEE Trans. Ind. Informat., vol. 7, no. 1, pp. 18–29, Feb. 2011.Y. Tian and D. Levy, “Compensation for control packet dropout in networked control systems,” Inform. Sci., vol. 178, no. 5, pp. 1263–1278, 2008.Y. Zhao, G. Liu, and D. Rees, “Modeling and stabilization of continuous-time packet-based networked control systems.” IEEE Trans. Syst., Man, Cybern. B, vol. 39, no. 6, pp. 1646–1652, Dec. 2009.X. Zhao, S. Fei, and C. Sun, “Impulsive controller design for singular networked control systems with packet dropouts,” Int. J. Control, Autom., and Syst., vol. 7, no. 6, pp. 1020–1025, 2009.H. Gao and T. Chen, “H ∞ estimation for uncertain systems with limited communication capacity,” IEEE Trans. Autom. Control, vol. 52, no. 11, pp. 2070–2084, 2007.S. Oh, L. Schenato, P. Chen, and S. Sastry, “Tracking and coordination of multiple agents using sensor networks: System design, algorithms and experiments,” Proc. of the IEEE, vol. 95, no. 1, pp. 234–254, 2007.M. Moayedi, Y. Foo, and Y. Soh, “Optimal and suboptimal minimum-variance filtering in networked systems with mixed uncertainties of random sensor delays, packet dropouts and missing measurements,” Int. J. Control, Autom., and Syst., vol. 8, no. 6, pp. 1179–1188, 2010.W. Zhang, M. Branicky, and S. Phillips, “Stability of networked control systems,” IEEE Control Syst. Mag., vol. 21, no. 1, pp. 84–99, 2001.J. Hespanha, P. Naghshtabrizi, and Y. Xu, “A survey of recent results in networked control systems,” Proc. of the IEEE, vol. 95, no. 1, pp. 138–162, 2007.J. Baillieul and P. Antsaklis, “Control and communication challenges in networked real-time systems,” Proc. of the IEEE, vol. 95, no. 1, pp. 9–28, 2007.P. Garcia, P. Castillo, R. Lozano, and P. Albertos, “Robustness with respect to delay uncertainties of a predictor-observer based discrete-time controller,” Proc. of the 45th IEEE Conf. on Decision and Control, pp. 199–204, 2006.C. Lien, “Robust observer-based control of systems with state perturbations via LMI approach,” IEEE Trans. Autom. Control, vol. 49, no. 8, pp. 1365–1370, 2004.A. Sala, “Computer control under time-varying sampling period: an LMI gridding approach,” Automatica, vol. 41, no. 12, pp. 2077–2082, Dec. 2005.J. Li, Q. Zhang, Y. Wang, and M. Cai, “H ∞ control of networked control systems with packet disordering,” IET Control Theory Appl., vol. 3, no. 11, pp. 1463–1475, March 2009.Y. Zhao, G. Liu, and D. Rees, “Improved predictive control approach to networked control systems,” IET Control Theory Appl., vol. 2, no. 8, pp. 675–681, Aug. 2008.K. Astrom, “Event based control,” Analysis and Design of Nonlinear Control Systems, pp. 127–147, 2007.A. Cuenca, P. García, K. Arzén, and P. 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Development and evaluation of methods for control and modelling of multiple-input multiple-output systems

In control, a common type of system is the multiple-input multiple-output (MIMO) system, where the same input may affect multiple outputs, or conversely, the same output is affected by multiple inputs. In this thesis two methods for controlling MIMO systems are examined, namely linear quadratic Gaussian (LQG) control and decentralized control, and some of the difficulties associated with them.One difficulty when implementing decentralized control is to decide which inputs should control which outputs, also called the input-output pairing problem. There are multiple ways to solve this problem, among them using gramian based measures, which include the Hankel interaction index array, the participation matrix and the Σ2 method.\ua0 These methods take into account system dynamics as opposed to many other methods which only consider the steady-state system. However, the gramian based methods have issues with input and output scaling. Generally, this is handled by scaling all inputs and outputs to have equal range. However, in this thesis it is demonstrated how this can cause an incorrect pairing. Furthermore, this thesis examines other methods of scaling the gramian based measures, using either row or column sums, or by utilizing the Sinkhorn-Knopp algorithm. It is shown that there are considerable benefits to be gained from the alternative scaling of the gramian based measures, especially when using the Sinkhorn-Knopp algorithm. The use of this method also has the advantage that the results are completely independent of the original scaling of the inputs and outputs.An expansion to the decentralized control structure is the sparse control, in which a decentralized controller is expanded to include feed-forward or MIMO blocks. In this thesis we explore how to best use the gramian based measures to find sparse control structures, and propose a method which demonstrates considerable improvement compared to existing methods of sparse control structure design.A prerequisite to implementing control configuration methods is an understanding of the processes in question. In this thesis we examine the pulp refining process and design both static and dynamic models for pulp and paper properties such as shives width, fiber length and tensile index, and various available inputs. We demonstrate that utilizing internal variables (primarily consistencies) estimated from temperature measurements yields improved results compared to using solely measured variables. The measurement data from the refiners is noisy, sometimes sparse and generally irregularly sampled. This thesis discusses the challenges posed by these constraints and how they can be resolved.\ua0\ua0 An alternative way to control a MIMO system is to implement an LQG controller, which yields a single control structure for the entire system using a state based controller. It has been proposed that LQG control can be an effective control scheme to be used on networked control systems with wireless channels. These channels have a tendency to be unreliable with packet delays and packet losses. This thesis examines how to implement an LQG controller over such unreliable communication channels, and derives the optimal controller minimizing the cost function expressed in actuated controls.When new methods of control system design and analysis are introduced in the control engineering field, it is important to compare the new results with existing methods. Often this requires application of the methods on examples, and for this purpose benchmark processes are introduced. However, in many areas of control engineering research the number of examples are relatively few, in particular when MIMO systems are considered. For a thorough assessment of a method, however, as large number of relevant models as possible should be used. As a remedy, a framework has been developed for generating linear MIMO models based on predefined system properties, such as model type, size, stability, time constants, delays etc. This MIMO generator, which is presented in this thesis, is demonstrated by using it to evaluate the previously described scaling methods for the gramian based pairing methods

Jump state estimation with multiple sensors with packet dropping and delaying channels

This work addresses the design of a state observer for systems whose outputs are measured through a communication network. The measurements from each sensor node are assumed to arrive randomly, scarcely and with a time-varying delay. The proposed model of the plant and the network measurement scenarios cover the cases of multiple sensors, out-of-sequence measurements, buffered measurements on a single packet and multirate sensor measurements. A jump observer is proposed that selects a different gain depending on the number of periods elapsed between successfully received measurements and on the available data. A finite set of gains is pre-calculated offline with a tractable optimisation problem, where the complexity of the observer implementation is a design parameter. The computational cost of the observer implementation is much lower than in the Kalman filter, whilst the performance is similar. Several examples illustrate the observer design for different measurement scenarios and observer complexity and show the achievable performance

Renegotiation based dynamic bandwidth allocation for selfsimilar VBR traffic

The provision of QoS to applications traffic depends heavily on how different traffic types are categorized and classified, and how the prioritization of these applications are managed. Bandwidth is the most scarce network resource. Therefore, there is a need for a method or system that distributes an available bandwidth in a network among different applications in such a way that each class or type of traffic receives their constraint QoS requirements. In this dissertation, a new renegotiation based dynamic resource allocation method for variable bit rate (VBR) traffic is presented. First, pros and cons of available off-line methods that are used to estimate selfsimilarity level (represented by Hurst parameter) of a VBR traffic trace are empirically investigated, and criteria to select measurement parameters for online resource management are developed. It is shown that wavelet analysis based methods are the strongest tools in estimation of Hurst parameter with their low computational complexities, compared to the variance-time method and R/S pox plot. Therefore, a temporal energy distribution of a traffic data arrival counting process among different frequency sub-bands is considered as a traffic descriptor, and then a robust traffic rate predictor is developed by using the Haar wavelet analysis. The empirical results show that the new on-line dynamic bandwidth allocation scheme for VBR traffic is superior to traditional dynamic bandwidth allocation methods that are based on adaptive algorithms such as Least Mean Square, Recursive Least Square, and Mean Square Error etc. in terms of high utilization and low queuing delay. Also a method is developed to minimize the number of bandwidth renegotiations to decrease signaling costs on traffic schedulers (e.g. WFQ) and networks (e.g. ATM). It is also quantified that the introduced renegotiation based bandwidth management scheme decreases heavytailedness of queue size distributions, which is an inherent impact of traffic self similarity. The new design increases the achieved utilization levels in the literature, provisions given queue size constraints and minimizes the number of renegotiations simultaneously. This renegotiation -based design is online and practically embeddable into QoS management blocks, edge routers and Digital Subscriber Lines Access Multiplexers (DSLAM) and rate adaptive DSL modems

Novel Strategies to design Controllers and State Predictors based on Disturbance Observers

[ES] Los sistemas de ingeniería o físicos suelen ser inciertos. Su incertidumbre se manifiesta cuando el sistema muestra comportamientos que son relativamente diferentes a los que su modelo predice; estando principalmente causada por: errores de modelado; dinámicas desconocidas; cambios en las propiedades del sistema; interacciones aleatorias con otros sistemas; o cambios en las condiciones de operación. Durante los últimos 40 años, se ha demostrado reiteradamente que las incertidumbres de los sistemas pueden tener efectos muy negativos sobre el comportamiento de un controlador si éstas no se consideran adecuadamente sus formulaciones matemáticas. Por esta razón, una parte importante de la investigación actual está centrada en este tema; buscando las formas mas adecuadas para representar matemáticamente las incertidumbres de los sistemas, así como buscando nuevas herramientas matemáticas que permitan hacer uso de ésta representación de la incertidumbre con el objetivo de diseñar algoritmos de control robustos. En esta tesis se presentan nuevas aportaciones en esta línea. Concretamente, se desarrollan nuevas metodologías para diseñar controladores (DOBCs) y predictores (DOBPs) para sistemas dinámicos inciertos basados en observadores de perturbaciones. La principal aportación es demostrar que los DOBCs se pueden sintetizar desde un enfoque de control óptimo; siendo su principal criterio de diseño el de aproximar la -irrealizable- señal de control óptima que minimiza un índice de coste cuadrático sujeto a un modelo dinámico lineal (LTI). Este nuevo enfoque de diseño es indistintamente válido para modelos SISO/MIMO con múltiples o únicas perturbaciones. Además permite un ajuste del controlador muy intuitivo gracias a las matrices de ponderación del coste. De forma similar; los DOBPs se construyen con el objetivo de aproximar la solución temporal un sistema dinámico perturbado. Con el objetivo de contextualizar la aportación, el documento también incluye un breve resumen de los principales métodos de control robusto y el impacto que han tenido en la revolución tecnológica del siglo XXI; algunas discusiones sobre la utilidad de los modelos LTI perturbados para representar sistemas dinámicos inciertos; y algunas relaciones, comparaciones y simulaciones numéricas de los métodos propuestos con otras técnicas de control.[CA] Els sistemes d'enginyeria o físics solen ser incerts. La seua incertesa es manifesta quan el sistema mostra comportaments que són relativament diferents als que el seu model prediu; sent principalment causada per: errors de modelatge; dinàmiques desconegudes; canvis en les propietats del sistema; interaccions aleatòries amb altres sistemes; o canvis en les condicions d'operació. Durant els últims 40 anys, s'ha demostrat reiteradament que les incerteses dels sistemes poden tindre efectes molt negatius sobre el comportament d'un controlador si aquestes no es consideren adequadament les seues formulacions matemàtiques. Per aquesta raó, una part important de la investigació actual està centrada en aquest tema; buscant les formes mes adequades per a representar matemàticament les incerteses dels sistemes, així com buscant noves tècniques matemàtiques que permeten fer ús d'aquesta representació de la incertesa amb l'objectiu de dissenyar algorismes de control robustos. En aquesta tesi es presenten noves aportacions en aquesta línia. Concretament, es desenvolupen noves metodologies per a dissenyar controladors (DOBCs) i predictors (DOBPs) per a sistemes dinàmics incerts basats en observadors de pertorbacions. La principal aportació és demostrar que els DOBCs es poden sintetitzar des d'un punt de vista de control òptim; sent el seu principal criteri de disseny el d'aproximar la -irrealitzable- senyal de control òptima que minimitza un índex de cost quadràtic restringit a un model dinàmic lineal (LTI). Aquest nou plantejament és indistintament vàlid per a models SISO/MIMO amb múltiples o úniques pertorbacions. A més permet un ajust del controlador molt intuïtiu gràcies a les matrius de ponderació del cost. De manera similar; els DOBPs es construeixen amb l'objectiu d'aproximar la solució temporal un sistema dinàmic pertorbat. Amb l'objectiu de contextualitzar l'aportació, el document també inclou un breu resum dels principals mètodes de control robust i l'impacte que han tingut en la revolució tecnològica del segle XXI; algunes discussions sobre la utilitat dels models LTI pertorbats per a representar sistemes dinàmics incerts; i algunes relacions, comparacions i simulacions numèriques dels mètodes proposats amb altres tècniques de control.[EN] Engineering or physical systems are used to be uncertain. Its uncertainty is manifested whenever the system shows behaviors that are relatively different than the ones predicted by its model; being mostly caused by: modeling errors; unknown dynamics; changes in the system properties; random interactions with other systems; or changes in the operating conditions. Through the last 40 years, it has been persistently proved that the system uncertainties could have very negative effects in the performance of a feedback regulator if they are not properly considered in the mathematical formulations of the employed algorithms. Thus, an important part of the recent research is focused on this topic; searching for the most appropriate ways to mathematically represent the system uncertainties and looking for new mathematical-tools that permit to make use of such uncertainty-representation in order to design robust control algorithms. In this thesis, new contributions in this line are provided. Concretely, novel methodologies to design Disturbance Observer-Based Controllers (DOBCs) and Predictors (DOBPs) for uncertain dynamic systems are developed. The main contribution is to show that the DOBCs can be constructed from an optimality-based approach, with the main objective of approximating the -unrealizable- optimal control signal that minimizes a quadratic-cost performance index subject to a LTI disturbed model constraint. This novel robust control design is indistinctly valid for SISO/MIMO models with single/multiple matched/mismatched disturbances; offering also a highly intuitive and versatile tuning through the weighting matrices. Similarly, the DOBPs are synthesized in order to approximate the time-domain solution of LTI disturbed models. For the sake of completeness, the document also includes a brief review of the main robust control methods and the impact that they have had on the technological revolution of the 21st century; some discussions about the usefulness of the LTI disturbed models for representing uncertain dynamic systems; and different relationships, comparisons and numerical simulations, of the proposed methods with other control approaches.Castillo Frasquet, A. (2021). Novel Strategies to design Controllers and State Predictors based on Disturbance Observers [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/165034TESI

Annual Reviews in Control

There is growing interest in the use of control theory for interdisciplinary applications, where data may be sparse or missing, be non-uniformly sampled, have greater uncertainty, and where there is no opportunity to collect repeat measurements. In such applications, problems posed by observational data and the issue of missing or irregular data need to be considered. We present a review on dealing with observational, missing and irregular data for control applications. This considers the following issues: (i) how to identify a system model from observational data subject to missing measurements, (ii) how to determine control inputs when output data includes missing measurements, and (iii) how to ensure stability when future update times may be missed. Dealing with observational data and missing measurements is a key problem within the statistics literature, so we introduce statistical methods for dealing with this type of data. We aim to enable the integration of well-developed statistical methods of dealing with missing data into control theory. An example problem of using anticoagulants to control the blood clotting speed of patients is used throughout the paper

Modeling and Prediction in Diabetes Physiology

Diabetes is a group of metabolic diseases characterized by the inability of the organism to autonomously regulate the blood glucose levels. It requires continuing medical care to prevent acute complications and to reduce the risk of long-term complications. Inadequate glucose control is associated with damage, dysfunction and failure of various organs. The management of the disease is non trivial and demanding. With today’s standards of current diabetes care, good glucose regulation needs constant attention and decision-making by the individuals with diabetes. Empowering the patients with a decision support system would, therefore, improve their quality of life without additional burdens nor replacing human expertise. This thesis investigates the use of data-driven techniques to the purpose of glucose metabolism modeling and short-term blood-glucose predictions in Type I Diabetes Mellitus (T1DM). The goal was to use models and predictors in an advisory tool able to produce personalized short-term blood glucose predictions and on-the-spot decision making concerning the most adequate choice of insulin delivery, meal intake and exercise, to help diabetic subjects maintaining glycemia as close to normal as possible. The approaches taken to describe the glucose metabolism were discrete-time and continuous-time models on input-output form and statespace form, while the blood glucose short-term predictors, i.e., up to 120 minutes ahead, used ARX-, ARMAX- and subspace-based prediction

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

A growing trend for information technology is to not just react to changes, but anticipate them as much as possible. This paradigm made modern solutions, such as recommendation systems, a ubiquitous presence in today's digital transactions. Anticipatory networking extends the idea to communication technologies by studying patterns and periodicity in human behavior and network dynamics to optimize network performance. This survey collects and analyzes recent papers leveraging context information to forecast the evolution of network conditions and, in turn, to improve network performance. In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios. Finally, we consider open challenges and research directions to make anticipatory networking part of next generation networks

Quadratic estimation for stochastic systems in the presence of random parameter matrices, time-correlated additive noise and deception attacks

This research was suported by the ``Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación'' of Spain and the European Regional Development Fund [grant number PID2021-124486NB-I00].Networked systems usually face different random uncertainties that make the performance of the least-squares (LS) linear filter decline significantly. For this reason, great attention has been paid to the search for other kinds of suboptimal estimators. Among them, the LS quadratic estimation approach has attracted considerable interest in the scientific community for its balance between computational complexity and estimation accuracy. When it comes to stochastic systems subject to different random uncertainties and deception attacks, the quadratic estimator design has not been deeply studied. In this paper, using covariance information, the LS quadratic filtering and fixed-point smoothing problems are addressed under the assumption that the measurements are perturbed by a time-correlated additive noise, as well as affected by random parameter matrices and exposed to random deception attacks. The use of random parameter matrices covers a wide range of common uncertainties and random failures, thus better reflecting the engineering reality. The signal and observation vectors are augmented by stacking the original vectors with their second-order Kronecker powers; then, the linear estimator of the original signal based on the augmented observations provides the required quadratic estimator. A simulation example illustrates the superiority of the proposed quadratic estimators over the conventional linear ones and the effect of the deception attacks on the estimation performance.Ministerio de Ciencia e Innovación MICINNEuropean Regional Development Fund PID2021-124486NB-I00 ERDFAgencia Estatal de Investigación AE