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While the existing thermomechanical constitutive models can predict the behavior of SMA-actuated systems in most cases, in this study, we have shown that there are certain situations in which these models are not able to predict the behavior of SMAs. To this end, a rotary SMA-actuated robotic arm is modeled using the existing constitutive models. The model is verified against the experimental results to document that under certain conditions, the model is not able to predict the behavior of the SMA-actuated manipulator. Such cases most often occur when the temperature and stress of the SMA wire change simultaneously. The constitutive model discrepancy is also studied experimentally using a dead-weight that is actuated by an SMA wire. Subsequently, an enhanced phenomenological model is developed. The enhanced model is able to predict the behavior of SMAs under complex thermomechanical loadings. For the SMA-actuated robotic arm, several control methods are designed through simulations. A position-based PID controller is designed first, and it is found that this controller cannot perform well for all the desired angular positions(set-points). A Variable Structure Control (VSC) based on the angular position and velocity is presented that has a relatively better erformance for all the set-points. To improve the erformance of the VSC, in terms of the steady state error, an Extended Kalman Filter is designed and used to modify the VSC design. The modified VSC is based on the angular position and angular velocity of the actuator and the estimated temperature of the SMA wire. Furthermore, a Sliding Mode Controller is designed based on the stress of the SMA wire. Finally, a model-based Backstepping Controller is designed for the SMA-actuated arm. This model-bsed controller allows designing the controller parameters based on the parameters of the system. Additionally, the stability of the controller is studied. Using the Lyapunov stability analysis, it is shown that the model-based Backstepping Controller is able to asymptotically stabilize the system. / Ph. D.

Functional Electrical Stimulation (FES) is a technique that applies electrical currents to nervous tissue in order to actively induce muscle contraction. Recent research has shown that FES provides a promising treatment to restore functional tasks due to paralysis caused by spinal cord injury, head injury, and stroke, to mention a few. Therefore, the overarching goal of this research work is to develop FES controllers to enable patients with movement-disorder to control their limbs in a desired manner and, in particular, to aid Parkinson's patients to suppress hand tremor. In our effort to develop strategies for muscle stimulation control, we first implement a model-based control technique assuming that all the states are measurable. The Hill-type muscle model coupled with a simplified 2DoF model of the arm is used to study the performance of our proposed adaptive sliding mode controller for simulation purpose. However, in the more practical situations, human limb dynamics are extremely complicate and it is inadequate to use model based controllers, especially considering there are still technical limitations that allow in vivo measurements of muscle activity. To tackle these challenges, we have developed output feedback adaptive control approaches for a class of unknown multi-input multi-output systems. Such control strategies are first developed for linear systems, and then extended to the nonlinear case. The proposed controllers, supported by experimental results, require minimum knowledge of the system dynamics and avoid many restrictive assumptions typically found in the literature. Therefore, we expect that the results introduced in this dissertation can provide a solution for a wide class of nonlinear uncertain systems, with focus on practical issues such as partial state measurement and the presence of mismatched uncertainties. / Ph. D.

In this master’s thesis, a turbine model and a common control structure for theturbocharger for SI and CI-engines is developed. To design the control structure,simulations are done on an existing diesel engine model with VGT. In order tobe able to make simulations for engines with a wastegated turbine, the model isextended to include mass flow and turbine efficiency for that configuration. Thedeveloped model has a mean absolute relative error of 3.6 % for the turbine massflow and 7.4 % for the turbine efficiency. The aim was to control the intake manifoldpressure with good transients and to use the same control structure for VGTand wastegate. By using a common structure, development and calibration timecan be reduced. The non-linearities have been reduced by using an inverted turbinemodel in the control structure, which consists of a PI-controller with feedforward.The controller can be tuned to give a fast response for CI engines and a slowerresponse but with less overshoot for SI engines, which is preferable.

The potential of carbon emission regulations applied to an individual building will encourage building owners to purchase utility-provided green power or to employ onsite renewable energy generation. As both cases are based on intermittent renewable energy sources, demand side control is a fundamental precondition for maximizing the effectiveness of using renewable energy sources. Such control leads to a reduction in peak demand and/or in energy demand variability, therefore, such reduction in the demand profile eventually enhances the efficiency of an erratic supply of renewable energy. The combined operation of active thermal energy storage and passive building thermal mass has shown substantial improvement in demand-side control performance when compared to current state-of-the-art demand-side control measures. Specifically, "model-based" optimal control for this operation has the potential to significantly increase performance and bring economic advantages. However, due to the uncertainty in certain operating conditions in the field its control effectiveness could be diminished and/or seriously damaged, which results in poor performance. This dissertation pursues improvements of current demand-side controls under uncertainty by proposing a robust supervisory demand-side control strategy that is designed to be immune from uncertainty and perform consistently under uncertain conditions. Uniqueness and superiority of the proposed robust demand-side controls are found as below: a. It is developed based on fundamental studies about uncertainty and a systematic approach to uncertainty analysis. b. It reduces variability of performance under varied conditions, and thus avoids the worst case scenario. c. It is reactive in cases of critical "discrepancies" observed caused by the unpredictable uncertainty that typically scenario uncertainty imposes, and thus it increases control efficiency. This is obtainable by means of i) multi-source composition of weather forecasts including both historical archive and online sources and ii) adaptive Multiple model-based controls (MMC) to mitigate detrimental impacts of varying scenario uncertainties. The proposed robust demand-side control strategy verifies its outstanding demand-side control performance in varied and non-indigenous conditions compared to the existing control strategies including deterministic optimal controls. This result reemphasizes importance of the demand-side control for a building in the global carbon economy. It also demonstrates a capability of risk management of the proposed robust demand-side controls in highly uncertain situations, which eventually attains the maximum benefit in both theoretical and practical perspectives.

the 18th World Congress The International Federation of Automatic Control, Milano (Italy), August 28 - September 2, 2011

The implementation of automated systems in manufacturing industries increases efficiency, precision, and safety by reducing human intervention, errors, and waste. Variable loads can cause several problems for automation systems. One of the most significant challenges is maintaining the stability and precision of the production process despite changing load conditions. These variable loads can lead to unstable systems or failures, causing an increase in errors, reduced efficiency, and lower product quality. It is essential to design control systems that can adapt to changing load conditions and maintain stable and precise operation under all circumstances. To address this problem, this thesis presents an adaptive controller based on load identification and gain scheduling, to replace the standard FOC consisting of regular PI-controllers. The load estimator is used to estimate the external load with relatively small RMSD values, while the ain scheduler adjusts the controller gains based on the estimated load. Other controllers are also explored, such as an angular velocity error-based adaptive controller. The results shows that both proposed controllers perform better than the standard controller when the system is subject to variable external loads, however, the load estimator paired with the gain scheduled PI-controller performs best. / Automatiseringen, inom framförallt tillverkningsindustrin, ökar effektivitet, precision och säkerheten genom att minska den mänskliga faktorn, fel och kassationer. System som utsätts för variabel belastning kan orsaka flera olika problem för automationssystem. En av de största utmaningarna är att bibehålla stabilitet och precision i produktionsprocessen trots förändrade belastningsförhållanden. Dessa variabla belastningar kan leda till instabila system eller fel, vilket ökar felmängden, minskar effektiviteten och sänker produktkvaliteten. Därför är det viktigt att utforma styrsystem som kan anpassa sig till förändrade lastförhållanden och samtidigt upprätthålla stabil och precis drift under oavsett förutsättningar. För att lösa detta problem presenterar denna avhandling en adaptiv regulator baserad på lastidentifiering och gain-scheduling, för att ersätta den vanliga FOC som består av klassiska PI-regulatorer. Lastestimatorn används för att uppskatta den externa lasten med ett relativt litet RMSD, medan gain-scheduling justerar regulatorns förstärkning baserat på den uppskattade belastningen. Andra regulatorer utforskas också, såsom en adaptiv regulator baserad på fel i vinkelhastighet. Resultaten visar att båda föreslagna regulatorer presterar bättre än standardregulatorn när systemet utsätts för variabla externa belastningar, men att lastestimatorn tillsammans med gainscheduled PI-regulatorer presterar bäst.

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