In many  applications industrial robots perform the same motion  repeatedly. One way of compensating the repetitive part of the error  is by using iterative learning control (ILC). The ILC algorithm  makes use of the measured errors and iteratively calculates a  correction signal that is applied to the system. The main topic of the thesis is to apply an ILC algorithm to a  dynamic system where the controlled variable is not measured. A  remedy for handling this difficulty is to use additional sensors in  combination with signal processing algorithms to obtain estimates of  the controlled variable. A framework for analysis of ILC algorithms  is proposed for the situation when an ILC algorithm uses an estimate  of the controlled variable. This is a relevant research problem in  for example industrial robot applications, where normally only the  motor angular positions are measured while the control objective is  to follow a desired tool path. Additionally, the dynamic model of  the flexible robot structure suffers from uncertainties. The  behaviour when a system having these difficulties is controlled by  an ILC algorithm using measured variables directly is illustrated  experimentally, on both a serial and a parallel robot, and in  simulations of a flexible two-mass model. It is shown that the  correction of the tool-position error is limited by the accuracy of  the robot model. The benefits of estimation-based ILC is illustrated for cases when  fusing measurements of the robot motor angular positions with  measurements from an additional accelerometer mounted on the robot  tool to form a tool-position estimate. Estimation-based ILC is  studied in simulations on a flexible two-mass model and on a  flexible nonlinear two-link robot model, as well as in experiments  on a parallel robot. The results show that it is possible to improve  the tool performance when a tool-position estimate is used in the  ILC algorithm, compared to when the original measurements available  are used directly in the algorithm. Furthermore, the resulting  performance relies on the quality of the estimate, as expected. In the last part of the thesis, some implementation aspects of ILC  are discussed. Since the ILC algorithm involves filtering of signals  over finite-time intervals, often using non-causal filters, it is  important that the boundary effects of the filtering operations are  appropriately handled when implementing the algorithm. It is  illustrated by theoretical analysis and in simulations that the  method of implementation can have large influence over stability and  convergence properties of the algorithm. / Denna avhandling behandlar reglering genom iterativ inlärning, ILC  (från engelskans iterative learning control). Metoden har sitt  ursprung i industrirobottillämpningar där en robot utför samma  rörelse om och om igen. Ett sätt att kompensera för felen är genom  en ILC-algoritm som beräknar en korrektionssignal, som läggs på  systemet i nästa iteration. ILC-algoritmen kan ses som ett  komplement till det befintliga styrsystemet för att förbättra  prestanda. Det problem som särskilt studeras är då en ILC-algoritm appliceras  på ett dynamiskt system där reglerstorheten inte mäts. Ett sätt att  hantera dessa svårigheter är att använda ytterligare sensorer i  kombination med signalbehandlingsalgoritmer för att beräkna en  skattning av reglerstorheten som kan användas i ILC-algoritmen. Ett  ramverk för analys av skattningsbaserad ILC föreslås i avhandlingen.  Problemet är relevant och motiveras utifrån experiment på både en  seriell och en parallel robot. I konventionella robotstyrsystem  mäts endast de enskilda motorpositionerna, medan verktygspositionen  ska följa en önskad bana. Experimentresultat visar att en  ILC-algoritm baserad på motorpositionsfelen kan reducera dessa fel  effektivt. Dock behöver detta inte betyda en förbättrad  verktygsposition, eftersom robotmotorerna styrs mot felaktiga värden  på grund av att modellerna som används för att beräkna dessa  referensbanor inte beskriver den verkliga robotdynamiken helt. Skattningsbaserad ILC studeras både i simulering av en flexibel  tvåmassemodell och en olinjär robotmodell med flexibla leder, och i  experiment på en parallell robot. I studierna sammanvägs  motorpositionsmätningar med mätningar från en accelerometer på  robotverktyget till en skattning av verktygspositionen som används i  ILC-algoritmen. Resultaten visar att det är möjligt att förbättra  verktygspositionen med skattningsbaserad ILC, jämfört med när  motorpositionsmätningarna används direkt i  ILC-algoritmen. Resultatet beror också på skattningskvaliteten, som  förväntat. Slutligen diskuteras några implementeringsaspekter. Alla värden i  uppdateringssignalen läggs på systemet samtidigt, vilket gör det  möjligt att använda icke-kausal filtering där man utnyttjar framtida  signalvärden i filteringen. Detta gör att det är viktigt hur  randeffekterna (början och slutet av signalen) hanteras när man  implementerar ILC-algoritmen. Genom teoretisk analys och  simuleringsexempel illustreras att implementeringsmetoden kan ha  stor betydelse för egenskaperna hos ILC-algoritmen.

The exceptional feature of the brushless doubly-fed machine is the lack of need for frequent replacement of brushes. The inherent instability of this machine has to be overcome for its application in adjustable speed drives and variable speed generation systems. Specific objectives were: to study the characteristics of the machine pertinent to its application in adjustable speed drives and variable speed generation systems, to develop a stabilizer depending on the nature of the instability. The brushless doubly-fed machine was found to be unstable over much of the useful operating range. A digital feedback control was implemented using a combination of hardware and software elements/to stabilize the machine. The feedback system was a band pass filter. The software was developed with a processing time fast enough to match the speed of response required by the stabilizer to overcome the unstable oscillations. The performance of the machine was compared with and without the stabilizer to test its effectiveness. Stable operation was achieved over the entire operating region. / Graduation date: 1991

The effectiveness of linear control of a planar manipulator is presented for robot operation markedly exceeding the limits of linearity assumed in the design of the linear controller. Wolovich's frequency domain pole placement algorithm is utilized to derive the linear controller. The control scheme must include state estimation since only link position is measured in the planar manipulator studied. Extensive simulations have been conducted not only to verify the linear control design but also to examine the behavior of the controlled system when inputs greatly exceed those assumed for linear design. The results from these studies indicate the linear model performs exactly as designed. The non-linear realistic simulation reveals that the linear model results are obtained when the inputs do not exceed linearity limits. However, when large inputs are applied, the nature of the system response changes significantly. Regardless of the change in behavior, for the cases considered, there was no instability detected and steady-state values were realized with reasonable settling times which increased in length as the size of the inputs were increased. From the simulation results, it is concluded that the linear controller scheme studied is suitable for use in moving objects from one position to another but would not work well in the rapid drawing of lines and curves. / Graduation date: 1992

A new decentralized nonlinear controller for Robot Manipulators is presented in this thesis. Based on concepts of Lyapunov stability theory and some control ideas proposed in [3]-[7], we obtain continuous nonlinear decentralized control laws which guarantee position and velocity tracking to within an arbitrarily small error. Assumptions based on physical constraints of manipulators are made to guarantee the existence of the controller and asymptotic stability of the closed loop system. Simulations show how well this rather simple control scheme works on two of the links of the Puma 560 Manipulator. The main contribution of this thesis is that it extends the results of a class of complex centralized control algorithms to the decentralized robust control of interconnected nonlinear subsystems like robot manipulators. / Graduation date: 1992

TCP (Transmission Control Protocol) is a transport protocol designed for the wired Internet. In wireless networks packet losses occur more frequently due to the unreliability of the physical link. The main problem is that TCP treats all losses as congestion, which leads to a lower throughput. Ad hoc networks are multihop wireless networks of mobile nodes, where each node can allow other packets to pass through it. Topology changes often occur and may lead to packet losses and delays, which TCP misinterprets as congestion. We want to modify TCP to recognize the differences between link failure and congestion to improve the capacity. In our model we have built a connection in an ad hoc network where packet losses and partitions can be made. Simulation experiments show that we didn't get the problems we expected. This can be explained by low delays and because we buffered the packets during link failure. A simple modification of TCP was made and simulated, and showed that an improvement of performance is possible. More research should be done to make a modification of TCP that would further affect the throughput.

This thesis presents a control system for a walking machine leg. The leg is representative of one of the six legs required for a proposed walking machine based on the geometry of the darkling beetle. Each of the three joints is controlled by a DC servo motor mounted to the base of the leg. The speed of the motors is controlled with pulse width modulation. Feedback of joint positions is accomplished with potentiometers mounted on the actual joints. A five-point path, forming a rectangle in the global coordinate system, is used as a skeleton of the path of movement. Desired times and accelerations from point to point are used to develop the path of movement, which smoothes corners and velocity transitions along the path. To create a model of the dynamics of each joint, a constant motor speed is output and the joint velocity and joint angle are recorded. From several trials at several different motor speeds, relationships between the joint velocity, joint angle, and motor speed can be found. This data is then least squares fit in two dimensions to give two second order functions. The first function uses the desired joint angle to calculate the variance from the mean joint velocity. This variance is then added to the desired joint velocity and is used in the second function to calculate the needed motor signal. Feedback control is accomplished using a PID control system. Because of the high level of noise in the feedback signal, a digital noise filter is used. Both moving average and linear regression techniques are examined. Performance of the system is measured by comparing the actual path in Cartesian coordinates to the desired path of movement. The RMS error is taken along the path, during the time frame of the ideal system. The maximum Cartesian error along the path is also used in evaluation. To determine suitable feedback gain combinations, several experiments are run and evaluated. Data is plotted and suitable values are chosen for the feedback gains based on their performance and sensitivity to change in performance. The performance of the leg is measured for a basic rectangular path, the basic path with a variation in step angle, and the basic path with a constant body velocity. / Graduation date: 1992

Active insulin receptors (IR) phosphorylate insulin receptor substrate (IRS), but it is not clear whether IRS is phosphorylated mainly by IR at the plasma membrane or by internalized IR in the cytosol. In this thesis, structural identifiability analysis and parameter sensitivity analysis is performed for models of the first steps in the metabolic insulin signaling pathway. In particular, the identifiability of the kinetic parameters governing IRS phosphorylation are investigated. Given measurements of the relative increase in phosphorylation degree of IR and IRS, the structural identifiability analysis revealed that the parameters governing IRS phosphorylation are non-identifiable, but their ratio is identifiable. This is sufficient to study whether phosphorylation of IRS proceeds more rapidly by IR at the plasma membrane or by internalized IR in the cytosol. In the examined model structure, internalization of insulin receptors is shown to be necessary to reproduce the experimental data. Sensitivity analysis of the parameters governing IRS phosphorylation showed that many parameters need to be known in order to obtain ``practical identifiability'' of the interesting parameters.

An adaptive decentralized nonlinear controller for a robot manipulator is presented in this thesis. Based on the adaptive control schemes designed by Seraji [18], Dai [30], and Jimenez [31], we redesigned and further simplified the control algorithm and, as a consequence, we achieved better path tracking performance. The proposed adaptive controller is made of a PD feedback controller which has time varying gains, a feedforward compensator based on the idea of inverse dynamics, and an auxiliary signal. Due to its adaptive structure, the controller shows robustness against disturbances and unmodeled dynamics. In order to ensure asymptotic tracking we select a Lyapunov function such that the controller forces the negative definiteness of the time derivative of such a Lyapunov function. To do this, the tracking position and velocity error are penalized and used as a part of the adaptive control gain. The main advantages of this scheme are the comparably faster convergence of tracking error, relatively simpler structure, and smoother control activity. This controller only requires the position and angular speed measurement, it does not require any knowledge about the mathematical model of the robot manipulator. Simulation shows the capacity of this controller and its robustness against disturbances. / Graduation date: 1993

Model, Model-based or Receding-horizon Predictive Control (MPC or RHPC) is a successful and mature control strategy which has gained the widespread acceptance of both academia and industry. The basis of these control laws, which have been reported to handle quite complex dynamics, is to perform predictions of the system to be controlled by means of a model. A control profile is then computed to minimise some cost function defined in terms of the predictions and the hypothesised controls. It was soon realised that the first few predictive controllers failed to fulfil essential properties, such as the stability of the nominal closed-loop system. In addition, it was noticed that the discrepancies between the model and the true process, referred to as system uncertainty, can seriously affect the achieved performance. The robustness problem should, thus, be addressed. In this thesis, the problems of nominal stability and robustness are reviewed and investigated. In particular, the accomplishment of constraint specifications in the presence of various sources of uncertainty is a major objective of the methods developed throughout this PhD research. First of all, controllers which guarantee nominal stability, such as the CRHPC and the GPC∞, are highlighted and formulated, and 1-norm counterparts are obtained. The robustness of these strategies in the unconstrained case has been analysed, and it has been concluded that the infinite horizon approach often leads to more convenient performance and robustness results for typical choices of the tuning knobs. Then the constrained case has been undertaken, and min-max controllers based on the global uncertainty approach have been formulated for both 1-norm and 2-norm formulations. For these methods, a band updating algorithm has been suggested to modify the assumed uncertainty bounds on-line. Although both formulations provide similar results, which overcome the classical approach to robustness when constraints are specified, the 1-norm controllers are computationally more efficient, since the optimal control move sequence can be computed with a standard LP problem. Finally, a refinement of the min-max approach which includes the notion that feedback is present in the receding-horizon implementation of predictive controllers, termed as feedback min-max MPC, is shown to overcome some of the drawbacks of the standard min-max approach. / El Control Predictiu Basat en Models (Model, Model-based o Receding-horizon Predictive Control; MPC o RHPC) és una estratègia de control madura i de gran èxit, que ha assolit l'acceptació de les comunitats acadèmica i industrial. La base d'aquest tipus de lleis de control, la capacitat de les quals per treballar amb dinàmiques complexes s'ha documentat en la literatura, és realitzar prediccions del sistema a controlar mitjançant un model. A partir de les prediccions, es calcula un perfil de controls per tal de minimitzar un funció de cost definida en termes de les prediccions i dels controls futurs. Després de les primeres formulacions es van detectar las carències dels controladors predictius per satisfer determinades propietats essencials, com garantir l'estabilitat del sistema nominal en llaç tancat. A més, era ben conegut que les discrepàncies existents entre el model i el procés, denominades incertesa del sistema, podien afectar severament el rendiment. Calia, per tant, abordar el problema de la robustesa. En aquesta tesi es revisa i s'investiguen els problemes de l'estabilitat nominal i la robustesa. En particular, la satisfacció de les especificacions de restriccions en presència de diverses fonts d'incertesa és un objectiu principal dels mètodes desenvolupats al llarg d'aquesta recerca. En primer lloc, s'ha fet una revisió dels controladors que asseguren estabilitat nominal, com el CRHPC i el GPC∞, i s'han suggerit controladors equivalents en norma 1. A continuació, s'ha estudiat la robustesa d'aquestes estratègies en absència de restriccions i s'ha conclòs que l'aproximació d'horitzons infinits condueix, habitualment, a millors resultats pel que fa al rendiment i a la robustesa per a valors típics dels paràmetres de sintonia. Seguidament s'ha tractat el problema de la robustesa en presència de restriccions i s'han formulat controladors min-max, tant en norma 1 com en norma 2, basats en el concepte d'incertesa global. Per a aquests mètodes, s'ha proposat un algorisme d'actualització de les bandes que permet modificar les fites de la incertesa en línia. Tot i que ambdues formulacions proporcionen resultats semblants, que superen els mètodes clàssics de robustesa quan s'especifiquen restriccions, els controladors en norma 1 són més eficients des del punt de vista del temps de còmput, atès que el problema d'optimització es pot resoldre fent servir programació lineal. Finalment, s'han proposat nous controladors basats en un últim avanç de l'aproximació min-max que incorpora la noció que la realimentació és present en la implementació d'horitzó mòbil dels controladors predictius. Aquestes tècniques, anomenades feedback min-max MPC, permeten de superar alguns dels desavantatges de la formulació min-max estàndard. / El Control Predictivo Basado en Modelos (Model, Model-based o Receding-horizon Predictive Control; MPC o RHPC) es una estrategia de control madura y de gran éxito, que ha conseguido la aceptación de las comunidades académica e industrial. La base de este tipo de leyes de control, cuya capacidad para manejar dinámicas complejas se ha documentado en la literatura, es realizar predicciones del sistema a controlar por medio de un modelo. A partir de las predicciones, se calcula un perfil de controles para minimizar una función de coste definida en términos de las predicciones y de los controles futuros. Tras las primeras formulaciones se detectaron las carencias de los controladores predictivos para satisfacer determinadas propiedades esenciales, como garantizar la estabilidad del sistema nominal en lazo cerrado. Además, era bien sabido que las discrepancias existentes entre el modelo y el proceso, denominadas incertidumbre del sistema, podían afectar severamente al rendimiento. El problema de la robustez debía, por tanto, ser abordado. En esta tesis se revisan e investigan los problemas de estabilidad nominal y robustez. En particular, la satisfacción de las especificaciones de restricciones en presencia de varias fuentes de incertidumbre es un objetivo principal de los métodos desarrollados a lo largo de esta investigación. En primer lugar, se han revisado los controladores que aseguran estabilidad nominal, como el CRHPC y el GPC∞ y se han propuesto controladores equivalentes en norma 1. A continuación se ha estudiado la robustez de estas estrategias en ausencia de restricciones y se ha concluido que la aproximación de horizontes infinitos conduce, habitualmente, a mejores resultados en lo referente al rendimiento y a la robustez para valores típicos de los parámetros de sintonía. Seguidamente, se ha tratado el problema de la robustez en presencia de restricciones, y se han formulado controladores min-max, tanto en norma 1como en norma 2, basados en el concepto de incertidumbre global. Para estos métodos, se ha sugerido un algoritmo de actualización de las bandas que permite modificar las cotas de la incertidumbre en línea. Aunque ambas formulaciones proporcionan resultados similares, que superan al enfoque clásico de la robustez cuando se especifican restricciones, los controladores en norma 1 son más eficientes desde el punto de vista de tiempo de cómputo, puesto que el problema de optimización se puede resolver usando programación lineal. Finalmente, se han propuesto otros controladores basados en un último avance de la aproximación min-max que incorpora la noción de que la realimentación está presente en la implementación de horizonte móvil de los controladores predictivos. Estas técnicas, denominadas feedback min-max MPC, permiten superar algunas de las desventajas de la formulación min-max estándar.

This Bachelor thesis is about constructing a graphic control and monitoring system for a production line at a snacks factory. A PLC program was developed for a small section of the production line. The PC-based graphical program was developed with Proficy HMI SCADA iFix 4.0 and and the programming of the PLC was done with Proficy Machine Edition 5.6. / Examensarbetets uppgift var att ta fram ett grafiskt system för att övervaka och reglera en produktionslinje på en snacksfabrik. Det ingick också att ta fram ett PLC-program för en specifik sektion av produktionen. De PC-baserade grafiska processbilder som tagits fram har gjorts med programmet Proficy HMI SCADA iFix 4.0 och styrprogrammet är gjort med Proficy Machine Edition 5.6.