Hydrofoiling technology has existed for over a hundred years but has seen a significant acceleration in development lately. The lower water resistance significantly increases the propulsion energy efficiency, giving the technology the potential to contribute to global goals of reducing emissions. Fully submerged hydrofoils, in general, and single-strut hydrofoils, in particular, need a control system to maintain stability in flight. It makes for an interesting control system design challenge, with dynamics resembling an inverted pendulum with six degrees of freedom. In this study, two control systems were designed and tested to stabilize a simulated model of the FoilCart prototype while performing turning maneuvers at different velocities and handling changes in altitude and speed. The first controller was a static Linear-Quadratic Integral (LQI) controller with some additions, including anti-windup mechanisms, setpoint step smoothing, symmetric linearization, and error cascading. The second controller was a modified, adaptive version of the LQI controller that used gain scheduling to combine multiple LQI controllers, each designed for coordinated banking turns at different roll angles, interpolating between them at every time step based on the current roll angle setpoint. With one exception, both controllers successfully performed turning maneuvers with 10 and 20° roll angles at 7 and 8 m/s. While the adaptive controller did, in some cases, improve the system’s speed, reducing rise time and overshoot, it was also less reliable and made the boat crash in one case (20° roll angle at 7 m/s). The static controller, however, exceeded all expectations and could perform stable turning maneuvers with roll angles up to 40°. Adding anti-windup measures and setpoint step smoothing improved stability, while error cascading and symmetric linearization had only minor, yet positive, effects. In conclusion, with the mentioned enhancements, LQI control systems have great potential for stabilizing single-strut hydrofoiling vessels. Several openings for future work remain, from validating these results in actual prototype tests to robustness and disturbance rejection studies and exploring other ways of combining LQI control and gain scheduling. / Bärplan har funnits i över hundra år, men dess utveckling och spridning har accelerat ordentligt den senaste tiden. Det minskade vattenmotståndet ökar energieffektiviteten avsevärt och ger tekniken potential att bidra till de globala målen att minska utsläppen. Dränkta bärplan i stort, men speciellt de som bara har en vertikal koppling till skrovet, behöver styrsystem för att bibehålla stabiliteten när de flyger. Utvecklingen av styrsystem för dem är därför en intressant utmaning, med dynamik liknande en inverterad pendel med sex frihetsgrader. I denna studie utvecklades och testades två styrsystem för att stabilisera en simulerad modell av FoilCart-prototypen under svängar i olika hastigheter och förändringar i höjdled. Det första styrsystemet var ett statiskt linjär-kvadratiskt integrerande system med vissa tilläggsfunktioner: anti-windup-mekanismer, utjämning av referenssteg, symmetrisk linjärisering och kaskadkoppling av felet. Det andra styrsystemet var en modifierad, adaptiv version av det första systemet. Det använde gain scheduling för att kombinera flera LQI-kontrollenheter designade för koordinerade svängar med en viss rollvinkel vardera, och interpolerade mellan dem vid varje tidssteg baserat på det aktuella referensvärdet för rollvinkeln. Med ett undantag lyckades båda styrsystemen genomföra koordinerade svängar med rollvinklar på 10 och 20° i 7 och 8 m/s. Medan det adaptiva styrsystemet i vissa fall gav ett snabbare svar med kortare stigtid och mindre översläng, var det även mindre pålitligt och fick båten att välta i ett fall (20° rollvinkel i 7 m/s). Det statiska styrsystemet överträffade dock alla förväntningar, och klarade att genomföra stabila svängar med upp till 40° rollvinkel. Tilläggsfunktionerna med anti-windup-mekanismer och utjämning av referenssteg förbättrade stabiliteten, medan kaskadkoppling av felet och symmetrisk linjärisering hade endast små, men positiva, effekter. Sammanfattningsvis har linjär-kvadratiska integrerande styrsystem med de nämnda tilläggsfunktionerna stor potential inom stabilisering av bärplansbåtar. Flera möjligheter för fortsatt arbete återstår, från validering av resultaten i faktiska prototyptester till utvärdering av robusthet och störningstålighet, samt utforskande av andra kombinationer av linjär-kvadratisk integrerande reglering och gain scheduling.

We consider the problem of Adaptive Control of finite-dimensional, stable, Linear Time Invariant (LTI) plants. Amongst such plants, the subclass regarding which an upper bound on the order is not known or which are known to be nonminimum phase (zeros in the unstable region) pose formidable problems in their own right. On one hand, if an upper bound on the order of the plant is not known, adaptive control usually involves some form of order estimation. On the other hand, when the plant is allowed to be either minimum phase or nonminimum phase, the adaptive control problem, as is well-known, becomes considerably-less tractable. In this study, the class of unknown plants considered is such that no information is available on the upper bound of the plant order and, further, the plant may be either minimum phase or nonminimum phase. Albeit known to be stable, such plants throw myriads of challenges in the context of adaptive control. Adaptive control involving such plants has been addressed [79] in a Model Reference Adaptive Control (MRAC) framework. There, the inputs and outputs of the unknown plant are the only quantities available by measurement in terms of which any form of modeling of the unknown plant may be made. Inputs to the reference model have been taken from certain restricted classes of bounded signals. In particular, the three classes of inputs considered are piecewise continuous bounded functions which asymptotically approach • a nonzero constant, • a sinusoid, and • a sinusoid with a nonzero shift. Moreover, the control law is such that adaptation is carried out at specific instants separated by progressively larger intervals of time. The schemes there have been proved to be e-optimal in the sense of a suitably formulated optimality criterion. If, however, the reference model inputs be extended to the class of piecewise continuous bounded functions, that would compound the complexity of the adaptive control problem. Only one attempt [78] in adaptive control in such a setting has come to our notice. The problem there has been tackled by an application of the theory of Pade Approximations to time moments of an LTI system. Based on a time moments estimation procedure, a simple adaptive scheme for Single-Input Single-Output (SISO) systems with only a cascade compensator has been reported. The first chapter is essentially meant to ensure that the problem we seek to address in the field of adaptive control indeed has scope for research. Having defined Adaptive Control, we selectively scan through the literature on LTI systems, with focus on MRAC. We look out in particular for studies involving plants of which not much is known regarding their order and systems which are possibly nonminimum phase. We found no evidence to assert that the problem of adaptive control of stable LTI systems, not necessarily minimum phase and of unknown upper bound on the order, was explored enough, save two attempts involving SISO systems. Taking absence of evidence (of in-depth study) for evidence of absence, we make a case for the problem and formally state it. We preview the thesis. We set two targets before us in Chapter 2. The first is to review one of the existing procedures attacking the problem we intend to address. Since the approach is based on the notion of time moments of an LTI system, and as we are to employ Pade Approximations as a tool, we uncover these concepts to the limited extent of our requirement. The adaptive procedure, Plant Command Modifier Scheme (PCMS) [78], for SISO plants is reported in some detail. It stands supported on an algorithm specially designed to estimate the time moments of an LTI system given no more than its input and output. Model following there has been sought to be achieved by matching the first few time moments of the reference model by the corresponding ones of the overall compensated plant. The plant time moment estimates have been taken to represent the unknown plant. The second of the goals is to analyze PCMS critically so that it may serve as a forerunner to our work. We conclude the chapter after accomplishing these goals. In Chapter 3, we devise a time moment estimator for SISO systems from a perspective which is conceptually equivalent to, yet functionally different from, that appropriated in [78]. It is a recipe to obtain estimates of time moments of a system by computing time moment estimates of system input and output signals measured up to current time. Pade approximations come by handy for this purpose. The lacunae exposed by a critical examination of PCMS in Chapter 2 guide us to progressively refine the estimator. Infirmities in the control part of PCMS too have come to light on our probing into it. A few of these will be fixed by way of fabricating two exclusively cascade compensators. We encounter some more issues, traceable to the estimator, which need redressal. Instead of directly fine-tuning the estimator itself, as is the norm, we propose the idea of 'estimating' the lopsidedness of the estimator by using it on the fully known reference model. This will enable us to effect corrections and obtain admissible estimates. Next, we explore the possibility of incorporating feedback compensation in addition to the existing cascade compensation. With output error minimization in mind, we come up with three schemes in this category. In the process, we anticipate the risk of instability due to feedback and handle it by means of an instability preventer with an inbuilt instability detector. Extensive simulations with minimum and rionminimum phase unknown plants employing the various schemes proposed are presented. A systematic study of simulation results reveals a dyad of hierarchies of progressively enhanced overall performance. One is in the sequence of the proposed schemes and the other in going for matching more and more moments. Based on our experiments we pick one of the feedback schemes as the best. Chapter 4 is conceived of as a bridge between SISO and multivariable systems. A transition from SISO to Multi-Input Multi-Output (MIMO) adaptive control is not a proposition confined to the mathematics of dimension-enhancement. A descent from the MIMO to the SISO case is expected to be relatively simple, though. So to transit as smoothly and gracefully as possible, some issues have to be placed in perspective before exploring multivariable systems. We succinctly debate on the efforts in pursuit of the exact vis-a-vis the accurate, and their implications. We then set some notations and formulate certain results which serve to unify and simplify the development in the subsequent three chapters. We list a few standard results from matrix theory which are to be of frequent use in handling multivariable systems. We derive control laws for Single-Input Multi-Output (SIMO) systems in Chapter 5. Expectedly, SIMO systems display traits of observability and uncontrollability. Results of illustrative simulations are furnished. In Chapter 6, we formulate control laws for Multi-Input Single-Output (MISO) systems. Characteristics of unobservability and controllability stand out there. We present case studies. Before actually setting foot onto MIMO systems, we venture to conjecture on what to expect there. We work out all the cascade and feedback adaptive schemes for square and nonsquare MIMO systems in Chapter 7. We show that MIMO laws when projected to MISO, SIMO and SISO cases agree with the corresponding laws in the respective cases. Thus the generality of our treatment of MIMO systems over other multivariable and scalar systems is established. We report simulations of instances depicting satisfactory performance and highlight the limitations of the schemes in tackling the family of plants of unknown upper bound on the order and possibly nonminimum phase. This forms the culmination of our exercise which took off from the reported work involving SISO systems [78]. Up to the end of the 7th chapter, we are in pursuit of solutions for the problem as general as in §1.4. For SISO systems, with input restrictions, the problem has been addressed in [79]. The laws proposed there carry out adaptation only at certain discrete instants; with respect to a suitably chosen cost, the final laws are proved to be e>optimal. In Chapter 8, aided by initial suboptimal control laws, we finally devise two algorithms with continuous-time adaptation and prove their optimality. Simulations with minimum and nonminimum phase plants reveal the effectiveness of the various laws, besides throwing light on the bootstrapping and auto-rectifying features of the algorithms. In the tail-piece, we summarize the work and wind up matters reserved for later deliberation. As we critically review the present work, we decant the take-home message. A short note on applications followed by some loud thinking as a spin-off of this report will take us to finis.

Transition delay in boundary-layer flows is achieved via reactive control of flow instabilities, i.e. Tollmien-Schlichting (TS) waves. Adaptive and model-based control techniques are investigated by means of direct numerical simulations (DNS) and experiments. The action of actuators localised in the wall region is prescribed based on localised measurement of the disturbance field; in particular, plasma actuators and surface hot-wire sensors are considered. Performances and limitations of this control approach are evaluated both for two-dimensional (2D) and three-dimensional (3D) disturbance scenarios. The focus is on the robustness properties of the investigated control techniques; it is highlighted that static model-based control, such as the linear-quadratic- Gaussian (LQG) regulator, is very sensitive to model-inaccuracies. The reason for this behaviour is found in the feed-forward nature of the adopted sensor/actuator scheme; hence, a second, downstream sensor is introduced and actively used to recover robustness via an adaptive filtered-x least-mean-squares (fxLMS) algorithm. Furthermore, the model of the flow required by the control algorithm is reduced to a time delay. This technique, called delayed-x least-mean-squares (dxLMS) algorithm, allows taking a step towards a self-tuning controller; by introducing a third sensor it is possible to compute on-line the suitable time-delay model with no previous knowledge of the controlled system. This self-tuning approach is successfully tested by in-flight experiments on a motor-glider. Lastly, the transition delay capabilities of the investigated control con- figuration are confirmed in a complex disturbance environment. The flow is perturbed with random localised disturbances inside the boundary layer and the laminar-to-turbulence transition is delayed via a multi-input-multi-output (MIMO) version of the fxLMS algorithm. A positive theoretical net-energy- saving is observed for disturbance amplitudes up to 2% of the free-stream velocity at the actuation location, reaching values around 1000 times the input power for the lower disturbance amplitudes that have been investigated. / I den här avhandlingen har reglertekniska metoder tillämpats för att försena omslaget från ett laminärt till ett turbulent gränsskikt genom att dämpa tillväxten av små instabiliteter, så kallade Tollmien-Schlichting vågor. Adaptiva och modellbaserade metoder för reglering av strömning har undersökts med hjälp av numeriska beräkningar av Navier-Stokes ekvationer, vindtunnelexperiment och även genom direkt tillämpning på flygplan. Plasmaaktuatorer och varmtrådsgivare vidhäftade på ytan av plattan eller vingen har använts i experimenten och modellerats i beräkningarna. Prestanda och begränsningar av den valda kontrollstrategin har utvärderats för både tvådimensionella och tredimensionella gränsskiktsinstabiliteter. Fokus har varit på metodernas robusthet, där vi visar att statiska metoder som linjär-kvadratiska regulatorer (LQG) är mycket känsliga för avvikelser från den nominella modellen. Detta beror främst på att regulatorer agerar i förkompenseringsläge (”feed-foward”) på grund av strömningens karaktär och placeringen av givare och aktuatorer. För att minska känsligheten mot avvikelser och därmed öka robustheten har en givare införts nedströms och en adaptiv fXLMS algoritm (filtered-x least-mean-squares) har tillämpats.                  Vidare har modelleringen av fXLMS-algoritmen förenklats genom att ersätta överföringsfunktionen mellan aktuatorer och givare med en lämplig tidsfördröjning.  Denna  metod som kallas för dxLMS (delayed-x least-mean-squares) kräver att ytterligare en givare införs långt uppströms för att kunna uppskatta hastigheten på de propagerande instabilitetsvågorna. Denna teknik har tillämpats framgångsrikt för reglering av gränsskiktet på vingen av ett segelflygplan. Slutligen har de reglertekniska metoderna testas för komplexa slumpmässiga tredimensionella störningar som genererats uppströms lokalt i gränsskiktet. Vi visar att en signifikant försening av laminärt-turbulentomslag äger rum med hjälp av en fXLMS algoritm. En analys av energibudgeten visar att för ideala aktuatorer och givare kan den sparade energiåtgången på grund av minskad väggfriktion vara upp till 1000 gånger större än den energi som använts för reglering.

Cette thèse propose des approches neuromimétiques d'identification et de commande avec des applications directes au Filtre Actif Parallèle (FAP) et au Moteur Synchrone à Aiment Permanent (MSAP). Une structure neuronale complète a été développée pour réaliser toutes les fonctionnalités d'un FAP pour compenser des harmoniques de courant. La phase instantanée et les composantes symétriques d'un système triphasé de tensions ou de courants ont été estimées avec une boucle à verrouillage de phase neuronale. L'identification des harmoniques de courant a été réalisée avec des réseaux de neurones de type Adaline opérant dans les différents repères. Plusieurs schémas de commande ont été développés pour réinjecter les courants de compensation à l'aide d'un onduleur. Ils sont basés sur des techniques neuromimétiques, sur la logique floue, ou sur leur association. Une approche neuronale a été développée pour commander une MSAP à distribution quelconque avec des contraintes prédéterminées réduisant les ondulations du couple. Elle consiste en des schémas de commande directe en couple ou en vitesse pour obtenir les courants statoriques optimaux qui donnent exactement le couple électromagnétique (ou la vitesse) désiré et qui réduisent au maximum les pertes par effet Joule. Ces commandes intègrent deux blocs neuronaux, l'un dédié au calcul des courants optimaux et l'autre pour assurer leur génération à travers un onduleur de tension. Toutes les approches neuromimétiques ont été validées par des tests de simulation et des essais expérimentaux. Des comparaisons avec les méthodes de commande classique démontrent des caractéristiques supérieures en termes de performance et de robustesse. / This thesis proposes Artificial Neural Networks (ANN) approaches for the identification and the control of an Active Power Filter (APF) and a Permanent-Magnet Synchronous Motor (PMSM). A completed neural architecture was developed for an APF for harmonic currents compensation. The instantaneous phase and the symmetrical components of a three-phase voltage or current were estimated with a neural phase Jock loop. The harmonic terms were identified by Adaline neural networks that estimate the instantaneous powers within different reference frames. Several intelligent techniques, based on neural networks, fuzzy logic or their association, were developed to control the inverter used to inject the harmonic currents phase-opposite. An original neural approach was also carried out for reducing the torque ripple of a non-sinusoidal PMSM. It consists in a direct torque or in a speed control schemes that elaborate the optimal stator currents which exactly give a desired electromagnetic torque or speed and which minimize the ohmic losses. The control schemes integrate two neural networks, one to calculate the optimal currents and one to ensure their generation through an inverter. The neural network approaches were all evaluated by simulated and experimental tests. The results confirm their excellent characteristics in terms of both performance and robustness. Comparisons with conventional methods prove their superiority.

Les systèmes non linéaires sont si diverses que des outils communs de contrôle sont difficiles à développer. La théorie du contrôle non linéaire nécessite une analyse mathématique rigoureuse pour motiver ses conclusions. Cette thèse aborde deux branches distinctes et bien importantes de la théorie du contrôle non linéaire: le contrôle des systèmes non-linéaires incertains et le contrôle des systèmes sous-actionnés.Dans la première partie, une classe de contrôleurs par mode glissant d’ordre supérieur (MGOS) robuste, basée sur la synthèse de Lyapunov, est développée pour le contrôle des systèmes non-linéaires incertains. Cette classe de contrôleurs est basée sur une classe de régulateurs qui stabilisent une pure chaîne d’intégrateurs en temps fini, et nécessite la connaissance a priori des bornes sur les incertitudes du système. Puis, afin d’éliminer la dépendance liée à la connaissance de ces bornes, un contrôleur par MGOS adaptatif est développé. Dans un deuxième temps, un contrôleur par MGOS homogène universel est développé où il est montré que le degré d’homogénéité peut être manipulé pour obtenir des avantages supplémentaires, tels que la bornitude de la commande, la garantie d’une amplitude minimale de la discontinuité de la commande et la convergence en temps fixe. Les performances des contrôleurs proposés ont été démontrées par des simulations et à travers des résultats expérimentaux sur un système pile à combustible.Dans la deuxième partie de la thèse, deux problèmes de commande de systèmes sous-actionnés sont étudiés. Le premier problème concerne le suivi de chemin global d’un robot mobile avec un point de visée. Le deuxième problème concerne la poursuite de trajectoire globale d’un bateau. Ces deux problèmes sont de nature distincte, cependant, ils sont soumis à des contraintes physiques similaires liées à la bornitude de la commande. Ainsi, les contrôleurs proposés sont basés sur l’utilisation de commandes saturées. Des simulations ont été effectuées pour démontrer les performances de ces contrôleurs. / Nonlinear systems are so diverse that generalized tools for control are difficult to develop. Nonlinear control theory requires rigorous mathematical analysis to justify its conclusions. This thesis addresses two distinct, yet important branches of nonlinear control theory: control of uncertain nonlinear systems and control of under-actuated systems.In the first part, a class of Lyapunov-based robust arbitrary higher order sliding mode (HOSM) controllers is developed for the control of uncertain nonlinear systems. This class of controllers is based on a class of controllers for finite-time stabilization of pure integrator chain, and requires the limits of the system uncertainty to be known a-priori. Then, in order to eliminate the dependence on the knowledge of these limits, an adaptive arbitrary HOSM controller is developed. Using this new class, a universal homogeneous arbitrary HOSM controller is developed and it is shown that the homogeneity degree can be manipulated to obtain additional advantages in the proposed controllers, such as bounded control, minimum amplitude of discontinuous control and fixed time convergence. The performance of the controllers has been demonstrated through simulations and experiments on a fuel cell system.In the next part, the control of two under-actuated systems is studied. The first control problem is the global path following of car-type robotic vehicle, using target-point. The second problem is the precise tracking of surface marine vessels. Both these problems are distinct in nature; however, they are subjected to similar physical constraints. The solutions proposed for these control problems use saturated controls, taking into account the physical bounds on the control inputs. Simulations have been performed to demonstrate the performance of these controllers.

近幾年來，有一些研究提出了只用單一一個管制圖即可同時偵測平均數和變異數。根據此目的，我們提出了加權平均損失管制圖，此管制圖是利用加權平均損失所建立的，在一個製成的目標值和平均數不一定相等時，它可同時監控一個製成的平均數和變異數。此加權平均損失統計量是應用一個加權因子，去調整製程平均和目標值的平方差和變異數的損失比重，所以此管制圖的效能比未經由加權因子調整過的管制圖還好。我們不只建立了固定管制參數(FP)加權平均損失管制圖，也建立了適應性加權平均損失管制圖，包括變動抽樣間隔(VSI)、變動樣本數與抽樣間隔(VSI)、變動管制參數(VP)；我們利用平均連串長度(ARL)來衡量固定管制參數管制圖的偵測績效，利用馬可夫鏈的方法計算偵測出異常訊息所需的平均時間(ATS)來衡量適應性管制圖的績效，並且做比較，我們發現適應性管制圖比固定管制參數管制圖的效能還要好。我們也利用最佳化技術建立最加適應性管制圖，當製成失控時，此最佳化管制圖能使ATS1最小。此外，當平均數和變異數的偏移幅度很小時，我們利用指數加權移動平均法(EWMA)建立EWMA加權平均損失管制圖，使其有較好的偵測力。這些我們所提出的管制圖，是只根據單一一個統計量所建立的，和X bar-S管制圖相比，有較好的效能，且和使用兩個管制圖同時偵測平均數和變異數相比，比較輕易理解且容易執行。 / In recent years, a few researchers had proposed different types of single charts that jointly monitor the process mean and the variation. In this project, we use the weighted average loss (WL) to construct WL control charts for monitoring the process mean and variance simultaneously while the target value may be different from the in-control mean. This statistic WL applied a weighted factor to adjust the weights of the loss due to the square of the deviation of the process mean from the target and the variance change. So the WL charts are more effective than unadjusted loss function charts. We not only construct the fixed parameters (FP) WL chart but also the adaptive WL charts which included variable sampling interval (VSI) WL chart, variable sample size and sampling interval (VSSI) WL chart and variable parameters (VP) WL chart. We calculate the average run length (ARL) for FP WL chart and using Markov chain approach to calculate the average time to signal (ATS) for adaptive WL charts to measure the performance and compare each other. From the comparison, we find the adaptive WL charts are more effective than the FP WL chart. We also proposed the optimal adaptive WL charts using an optimization technique to minimize ATS1 (ARL1) when the process was out-of-control. In addition, in order to detect the small shifts of the process mean and variance effectively, we construct the WL charts using the EWMA scheme. The proposed charts are based on only one statistic and are more effective than the X bar-S chart. And the WL charts are easy to understand and apply than using two charts for detecting the mean and variance shifts simultaneously.

No description available.

科学研究費補助金 研究種目:基盤研究(A)(2) 課題番号:08555101 研究代表者:早川 義一 研究期間:1996-1997年度

The CUSUM control charts have been widely used in detecting small process shifts since it was first introduced by Page (1954). And recent studies have shown that adaptive charts can improve the efficiency and performance of traditional Shewhart charts. To monitor the process mean and variance in a single chart, the loss function is used as a measure statistic in this article. The loss function can measure the process quality loss while the process mean and/or variance has shifted. This study combines the three features: adaption, CUSUM and the loss function, and proposes the optimal VSSI, VSI, and FP CUSUM Loss chart. The performance of the proposed charts is measured by using Average Time to Signal (ATS) and Average Number of Observations to Signal (ANOS). The ATS and ANOS calculations are based on Markov chain approach. The performance comparisons between the proposed charts and some existing charts, such as X-bar+S^2 charts and CUSUM X-bar+S^2 charts, are illustrated by numerical analyses and some examples. From the results of the numerical analyses, it shows that the optimal VSSI CUSUM Loss chart has better performance than the optimal VSI CUSUM Loss chart, optimal FP CUSUM Loss chart, CUSUM X-bar+S^2 charts and X-bar+S^2 charts. Furthermore, using a single chart to monitor a process is not only easier but more efficient than using two charts simultaneously. Hence, the adaptive CUSUM Loss charts are recommended in real process. / The CUSUM control charts have been widely used in detecting small process shifts since it was first introduced by Page (1954). And recent studies have shown that adaptive charts can improve the efficiency and performance of traditional Shewhart charts. To monitor the process mean and variance in a single chart, the loss function is used as a measure statistic in this article. The loss function can measure the process quality loss while the process mean and/or variance has shifted. This study combines the three features: adaption, CUSUM and the loss function, and proposes the optimal VSSI, VSI, and FP CUSUM Loss chart. The performance of the proposed charts is measured by using Average Time to Signal (ATS) and Average Number of Observations to Signal (ANOS). The ATS and ANOS calculations are based on Markov chain approach. The performance comparisons between the proposed charts and some existing charts, such as X-bar+S^2 charts and CUSUM X-bar+S^2 charts, are illustrated by numerical analyses and some examples. From the results of the numerical analyses, it shows that the optimal VSSI CUSUM Loss chart has better performance than the optimal VSI CUSUM Loss chart, optimal FP CUSUM Loss chart, CUSUM X-bar+S^2 charts and X-bar+S^2 charts. Furthermore, using a single chart to monitor a process is not only easier but more efficient than using two charts simultaneously. Hence, the adaptive CUSUM Loss charts are recommended in real process.

Esta Dissertação irá apresentar a utilização de técnicas de controle nãolinear, tais como o controle adaptativo e robusto, de modo a controlar um sistema de Eletroestimulação Funcional desenvolvido pelo laboratório de Engenharia Biomédica da COPPE/UFRJ. Basicamente um Eletroestimulador Funcional (Functional Electrical Stimulation FES) se baseia na estimulação dos nervos motores via eletrodos cutâneos de modo a movimentar (contrair ou distender) os músculos, visando o fortalecimento muscular, a ativação de vias nervosas (reinervação), manutenção da amplitude de movimento, controle de espasticidade muscular, retardo de atrofias e manutenção de tonicidade muscular. O sistema utilizado tem por objetivo movimentar os membros superiores através do estímulo elétrico de modo a atingir ângulos-alvo pré-determinados para a articulação do cotovelo. Devido ao fato de não termos conhecimento pleno do funcionamento neuro-motor humano e do mesmo ser variante no tempo, não-linear, com parâmetros incertos, sujeito a perturbações e completamente diferente para cada indivíduo, se faz necessário o uso de técnicas de controle avançadas na tentativa de se estabilizar e controlar esse tipo de sistema. O objetivo principal é verificar experimentalmente a eficácia dessas técnicas de controle não-linear e adaptativo em comparação às técnicas clássicas, de modo a alcançar um controle mais rápido, robusto e que tenha um desempenho satisfatório. Em face disso, espera-se ampliar o campo de utilização de técnicas de controle adaptativo e robusto, além de outras técnicas de sistemas inteligentes, tais como os algoritmos genéticos, provando que sua aplicação pode ser efetiva no campo de sistemas biológicos e biomédicos, auxiliando assim na melhoria do tratamento de pacientes envolvidos nas pesquisas desenvolvidas no Laboratório de Engenharia Biomédica da COPPE/UFRJ. / This dissertation will present the use of nonlinear control techniques, such as adaptive and robust control in order to design a Functional Electrical Stimulation (FES) system developed by Biomedical Engineering Laboratory at COPPE/UFRJ. Basically, a FES on the stimulation of motor nerves via skin electrodes in order to contract or stretch the muscles such that the amplitude and quality of the limbs movement can be maintained, reducing muscular atrophy as well. Consequently, the muscle strength can be improved and new neural pathways may be activated. Here, the goals of the proposed control system is to move the arm of the patient via electrical stimulation to achieve some desired trajectory related to the elbow angles of reference. Since we have a priori no deep knowledge of human neuro-motor model, the use of advanced and robust control schemes seems to be useful to stabilize this kind of systems which may be completely different for each individual, being time-varying, nonlinear, uncertain and subject to disturbances. The main objective is to experimentally verify the effectiveness of the proposed nonlinear and adaptive controllers when compared to classical ones in order to achieve faster, robust and better control performance. It is expected to spread the application of adaptive and robust controllers and other intelligent system tools, such as genetic algorithms, to the field of biological and biomedical engineering. Thus, we believe that the developed control system may help the improvement of the patients treatment involved in the research carried out by Biomedical Engineering Laboratory at COPPE/UFRJ.