Adaptive Estimation for Uncertain Nonlinear Systems with Measurement Noise: A Sliding-Mode Observer Approach

International audienceThis paper deals with the problem of adaptive estimation, i.e. the simultaneous estimation of the state and time-varying parameters, in the presence of measurement noise and state disturbances, for a class of uncertain nonlinear systems. An adap-tive observer is proposed based on a nonlinear time-varying parameter identification algorithm and a sliding-mode observer. The nonlinear time-varying parameter identification algorithm provides a fixed-time rate of convergence, to a neighborhood of the origin, while the sliding-mode observer ensures ultimate boundedness for the state estimation error attenuating the effects of the external disturbances. Linear matrix inequalities are provided for the synthesis of the adaptive observer while the convergence proofs are given based on the Lyapunov and Input-to-State Stability theory. Finally, some simulation results show the feasibility of the proposed approach

Energy efficient wireless sensor network protocols for monitoring and prognostics of large scale systems

In this work, energy-efficient protocols for wireless sensor networks (WSN) with applications to prognostics are investigated. Both analytical methods and verification are shown for the proposed methods via either hardware experiments or simulation. This work is presented in five papers. Energy-efficiency methods for WSN include distributed algorithms for i) optimal routing, ii) adaptive scheduling, iii) adaptive transmission power and data-rate control --Abstract, page iv

INTELLIGENT ESTIMATION IN DYNAMIC POSITIONING SYSTEMS OF MARINE VESSELS

Sustavi za dinamičko pozicioniranje plovnih objekata koriste se za održavanje njihove pozicije, smjera napredovanja i brzine, održavanje unaprijed definirane putanje gibanja, potpomognuto sidrenje i sl. Da bi se ove operacije uopće mogle provoditi, nužno je, između ostalog, omogućiti i određivanje precizne estimacije niskofrekventne pozicije, smjera napredovanja i brzine plovnog objekta, te estimaciju vjetrovnog i sporopromjenjivog opterećenja koje uzrokuju ostali vanjski poremećaji. U realnim sustavima za pozicioniranje plovnih objekata funkciju observera, tj. estimatora, ima neka od inačica Kalmanovog filtra koji ima već dugu tradiciju u brodskim sustavima upravljanja. U radu su analizirani klasični koncepti na kojima su temeljeni postojeći sustavi za dinamičko pozicioniranje te su istražene značajke dinamičkog pozicioniranja plovnih objekata s teoretske i praktične strane, posebno u dijelu koji se odnosi na problematiku filtriranja, identifikacije, estimacije i predikcije. Uočene su brojne prednosti, ali i nedostaci postojećih rješenja koji se mogu otkloniti primjenom novijih računalnih tehnologija kao što su algoritmi strojnog učenja i računalne inteligencije. Iz navedenih razloga, predložene su i konstruirane strukture statičkih, dinamičkih i hibridnih inteligentnih identifikatora i estimatora za potrebe identifikacije i estimacije u sustavima za dinamičko pozicioniranje. Od posebnog značaja su predloženi hibridni sustavi inteligentnih identifikatora i estimatora s proširenim Kalmanovim filtrom te inteligentni identifikatori za fuziju senzorskih informacija i rekonstrukciju signala u prekidu. Predloženi inteligentni identifikatori i estimatori su verificirani na realnim mjerenjima DP Log arhive dizaličara i cjevopolagača Saipem 7000 tijekom postupka polaganja cijevi na Projektu Ormen Lange (Norveška, 2006.).Dynamic positioning (DP) systems are used for maintaining position, heading and speed of the vessels, but also a predefined motion path, position mooring, etc. To ensure performing of these operations, it is necessary, among other things, to determine an accurate estimation of low-frequency position, heading and speed of the vessel. Additionally, it is necessary to ensure the estimation of wind and slowly-varying loads caused by other environmental disturbances. In actual DP systems, the vessel observer is usually an extended Kalman filter (EKF) which is traditionally used in marine control systems. In this doctoral thesis the classical base concepts of the existing commercial DP systems are analysed. Furthermore, the characteristics of DP systems are analysed both from the theoretical and practical point of view, especially in the part which is closely related to filtering, identification, estimation and prediction. Numerous advantages of existing solutions are identified, but also the several disadvantages which can be eliminated by using modern computational technologies such as machine learning and computational intelligence algorithms are pointed out. For these reasons, structures based on static, dynamic and hybrid intelligent identifiers and estimators have been proposed for the purpose of intelligent identification and estimation in DP systems. Proposed hybrid system of intelligent identifiers and estimators combined with EKF, as well as the intelligent identifiers for the sensor fusion and reconstruction of lost signals, are of particular interest. Intelligent identifiers and estimators are further adjusted, tested, and verified with real measurements from the DP Log archive of the heavy-lift and J-lay pipe vessel Saipem 7000

INTELLIGENT ESTIMATION IN DYNAMIC POSITIONING SYSTEMS OF MARINE VESSELS

Sustavi za dinamičko pozicioniranje plovnih objekata koriste se za održavanje njihove pozicije, smjera napredovanja i brzine, održavanje unaprijed definirane putanje gibanja, potpomognuto sidrenje i sl. Da bi se ove operacije uopće mogle provoditi, nužno je, između ostalog, omogućiti i određivanje precizne estimacije niskofrekventne pozicije, smjera napredovanja i brzine plovnog objekta, te estimaciju vjetrovnog i sporopromjenjivog opterećenja koje uzrokuju ostali vanjski poremećaji. U realnim sustavima za pozicioniranje plovnih objekata funkciju observera, tj. estimatora, ima neka od inačica Kalmanovog filtra koji ima već dugu tradiciju u brodskim sustavima upravljanja. U radu su analizirani klasični koncepti na kojima su temeljeni postojeći sustavi za dinamičko pozicioniranje te su istražene značajke dinamičkog pozicioniranja plovnih objekata s teoretske i praktične strane, posebno u dijelu koji se odnosi na problematiku filtriranja, identifikacije, estimacije i predikcije. Uočene su brojne prednosti, ali i nedostaci postojećih rješenja koji se mogu otkloniti primjenom novijih računalnih tehnologija kao što su algoritmi strojnog učenja i računalne inteligencije. Iz navedenih razloga, predložene su i konstruirane strukture statičkih, dinamičkih i hibridnih inteligentnih identifikatora i estimatora za potrebe identifikacije i estimacije u sustavima za dinamičko pozicioniranje. Od posebnog značaja su predloženi hibridni sustavi inteligentnih identifikatora i estimatora s proširenim Kalmanovim filtrom te inteligentni identifikatori za fuziju senzorskih informacija i rekonstrukciju signala u prekidu. Predloženi inteligentni identifikatori i estimatori su verificirani na realnim mjerenjima DP Log arhive dizaličara i cjevopolagača Saipem 7000 tijekom postupka polaganja cijevi na Projektu Ormen Lange (Norveška, 2006.).Dynamic positioning (DP) systems are used for maintaining position, heading and speed of the vessels, but also a predefined motion path, position mooring, etc. To ensure performing of these operations, it is necessary, among other things, to determine an accurate estimation of low-frequency position, heading and speed of the vessel. Additionally, it is necessary to ensure the estimation of wind and slowly-varying loads caused by other environmental disturbances. In actual DP systems, the vessel observer is usually an extended Kalman filter (EKF) which is traditionally used in marine control systems. In this doctoral thesis the classical base concepts of the existing commercial DP systems are analysed. Furthermore, the characteristics of DP systems are analysed both from the theoretical and practical point of view, especially in the part which is closely related to filtering, identification, estimation and prediction. Numerous advantages of existing solutions are identified, but also the several disadvantages which can be eliminated by using modern computational technologies such as machine learning and computational intelligence algorithms are pointed out. For these reasons, structures based on static, dynamic and hybrid intelligent identifiers and estimators have been proposed for the purpose of intelligent identification and estimation in DP systems. Proposed hybrid system of intelligent identifiers and estimators combined with EKF, as well as the intelligent identifiers for the sensor fusion and reconstruction of lost signals, are of particular interest. Intelligent identifiers and estimators are further adjusted, tested, and verified with real measurements from the DP Log archive of the heavy-lift and J-lay pipe vessel Saipem 7000

INTELLIGENT ESTIMATION IN DYNAMIC POSITIONING SYSTEMS OF MARINE VESSELS

Sustavi za dinamičko pozicioniranje plovnih objekata koriste se za održavanje njihove pozicije, smjera napredovanja i brzine, održavanje unaprijed definirane putanje gibanja, potpomognuto sidrenje i sl. Da bi se ove operacije uopće mogle provoditi, nužno je, između ostalog, omogućiti i određivanje precizne estimacije niskofrekventne pozicije, smjera napredovanja i brzine plovnog objekta, te estimaciju vjetrovnog i sporopromjenjivog opterećenja koje uzrokuju ostali vanjski poremećaji. U realnim sustavima za pozicioniranje plovnih objekata funkciju observera, tj. estimatora, ima neka od inačica Kalmanovog filtra koji ima već dugu tradiciju u brodskim sustavima upravljanja. U radu su analizirani klasični koncepti na kojima su temeljeni postojeći sustavi za dinamičko pozicioniranje te su istražene značajke dinamičkog pozicioniranja plovnih objekata s teoretske i praktične strane, posebno u dijelu koji se odnosi na problematiku filtriranja, identifikacije, estimacije i predikcije. Uočene su brojne prednosti, ali i nedostaci postojećih rješenja koji se mogu otkloniti primjenom novijih računalnih tehnologija kao što su algoritmi strojnog učenja i računalne inteligencije. Iz navedenih razloga, predložene su i konstruirane strukture statičkih, dinamičkih i hibridnih inteligentnih identifikatora i estimatora za potrebe identifikacije i estimacije u sustavima za dinamičko pozicioniranje. Od posebnog značaja su predloženi hibridni sustavi inteligentnih identifikatora i estimatora s proširenim Kalmanovim filtrom te inteligentni identifikatori za fuziju senzorskih informacija i rekonstrukciju signala u prekidu. Predloženi inteligentni identifikatori i estimatori su verificirani na realnim mjerenjima DP Log arhive dizaličara i cjevopolagača Saipem 7000 tijekom postupka polaganja cijevi na Projektu Ormen Lange (Norveška, 2006.).Dynamic positioning (DP) systems are used for maintaining position, heading and speed of the vessels, but also a predefined motion path, position mooring, etc. To ensure performing of these operations, it is necessary, among other things, to determine an accurate estimation of low-frequency position, heading and speed of the vessel. Additionally, it is necessary to ensure the estimation of wind and slowly-varying loads caused by other environmental disturbances. In actual DP systems, the vessel observer is usually an extended Kalman filter (EKF) which is traditionally used in marine control systems. In this doctoral thesis the classical base concepts of the existing commercial DP systems are analysed. Furthermore, the characteristics of DP systems are analysed both from the theoretical and practical point of view, especially in the part which is closely related to filtering, identification, estimation and prediction. Numerous advantages of existing solutions are identified, but also the several disadvantages which can be eliminated by using modern computational technologies such as machine learning and computational intelligence algorithms are pointed out. For these reasons, structures based on static, dynamic and hybrid intelligent identifiers and estimators have been proposed for the purpose of intelligent identification and estimation in DP systems. Proposed hybrid system of intelligent identifiers and estimators combined with EKF, as well as the intelligent identifiers for the sensor fusion and reconstruction of lost signals, are of particular interest. Intelligent identifiers and estimators are further adjusted, tested, and verified with real measurements from the DP Log archive of the heavy-lift and J-lay pipe vessel Saipem 7000

Systems Structure and Control

The title of the book System, Structure and Control encompasses broad field of theory and applications of many different control approaches applied on different classes of dynamic systems. Output and state feedback control include among others robust control, optimal control or intelligent control methods such as fuzzy or neural network approach, dynamic systems are e.g. linear or nonlinear with or without time delay, fixed or uncertain, onedimensional or multidimensional. The applications cover all branches of human activities including any kind of industry, economics, biology, social sciences etc