In wastewater treatment plants, the amount of ammonium is one example of a measure to determine the quality of the effluent wastewater. Ammonium is regarded as a hazardous chemical for aqueous ecosystems and can cause eutrophication due to its high nitrogen content. The ammonium content in the treated wastewater is controlled by aeration of the biological treatment stage, in which ammonium is converted to nitrate. The aeration process often accounts for the largest energy consumption of the wastewater treatment plant, which motivates automatic control solutions that can both aid in reducing the discharge of ammonium in the effluent and improve the energy efficiency of the aeration process. One such control technique currently used by several large municipal wastewater treatment plants in Sweden is ammonium-based aeration control. In this technique, the aeration process is controlled based on measurements of the effluent ammonium concentration. The purpose of the thesis was to study an extension of ammonium-based aeration control that could better adapt to daily, and often large, fluctuations in the influent load. The proposed method is to use an iterative algorithm to tune the set-point of the ammonium feedback controller. The objective is to, over a given time interval, achieve a flow-proportional mean of the effluent ammonium concentration close to a desired value for a wide range of influent loads. The method was tested by extensive simulations, and the results indicate that the iterative set-point tuning algorithm has the potential to offer a superior ability to achieve a desired flow-proportional mean at the end of a given evaluation period and, in some instances, energy savings compared to standard ammonium feedback control.

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This thesis presents model-based adaptive motion control algorithms for under-actuated aerial robotic manipulators combining a conventional multi-rotor Unmanned Aerial Vehicle (UAV) and a multi-link serial robotic arm. The resulting control problem is quite challenging due to the complexity of the combined system dynamics, under-actuation, and possible kinematic redundancy. The under-actuation imposes second-order nonholonomic constraints on the system motion and prevents independent control of all system degrees of freedom (DOFs). Desired reference trajectories can only be provided for a selected group of independent DOFs, whereas the references for the remaining DOFs must be determined such that they are consistent with the motion constraints. This restriction prevents the application of common model-based control methods to the problem of this thesis. Using insights from the system under-actuated dynamics, four motion control strategies are proposed which allow for semi-autonomous and fully-autonomous operation. The control algorithm is fully developed and presented for two of these strategies; its development for the other two configurations follows similar steps and hence is omitted from the thesis. The proposed controllers incorporate the combined dynamics of the UAV base and the serial arm, and properly account for the two degrees of under-actuation in the plane of the propellers. The algorithms develop and employ the second-order nonholonomic constraints to numerically determine motion references for the dependent DOFs which are consistent with the motion constraints. This is a unique feature of the motion control algorithms in this thesis which sets them apart from all other prior work in the literature of UAVmanipulators. The control developments follow the so-called method of virtual decomposition, which by employing a Newtonian formulation of the UAV-Manipulator dynamics, sidesteps the complexities associated with the derivation and parametrization of a lumped Lagrangian dynamics model. The algorithms are guaranteed to produce feasible control commands as the constraints associated with the under-actuation are explicitly considered in the control calculations. A method is proposed to handle possible kinematic redundancy in the presence of second-order motion constraints. The control design is also extended to include the propeller dynamics, for cases that such dynamics may significantly impact the system response. A Lyapunov analysis demonstrates the stability of the overall system and the convergence of the motion tracking errors. Experimental results with an octo-copter integrated with a 3 DOF robotic manipulator show the effectiveness of the proposed control strategies. / Thesis / Doctor of Philosophy (PhD)

A method to adapt the Generalized Predictive Control parameters to improve broadband disturbance rejection was developed and tested. The effect of the parameters on disturbance rejection has previously been poorly understood and a trial and error method was used to achieve adequate results. This dissertation provides insight on the effect of the parameters, as well as an adaptive tuning method to adjust them. The study begins by showing the effect of the four GPC parameters, the control and prediction horizons, control weighting &lambda , and order, on the disturbance rejection and control effort of a vibrating plate. It is shown that the effect of increases in the control and prediction horizon becomes negligible after a certain point. This occurs at nearly the same point for a variety of &lambda 's and orders, and hence they can be eliminated from the tuning space. The control effort and closed-loop disturbance rejection are shown to be highly dependant on &lambda and order, thereby becoming the parameters that need to be tuned. The behavior is categorized into various groups and further investigated. The pole and zero locations of the closed-loop system are examined to reveal how GPC gains control and how it can fail for non-minimum phase plants. A set of fuzzy logic modules is developed to adapt &lambda with order fixed, and conversely to adapt order with &lambda fixed. The effectiveness of the method is demonstrated in both numerical simulations and laboratory experiments. / Ph. D.

Tensegrity-membrane systems are a class of new bar-tendon-membrane systems. Such novel systems can be treated as extensions of tensegrity structures and are generally lightweight and deployable. These two major advantages enable tensegrity-membrane systems to become one of the most promising candidates for lightweight space structures and gossamer spacecraft. In this dissertation, modeling and control of tensegrity-membrane systems is studied. A systematic method is developed to determine the equilibrium conditions of general tensegrity-membrane systems. Equilibrium conditions can be simplified when the systems are in symmetric configurations. For one-stage symmetric systems, analytical equilibrium conditions can be determined. Three mathematical models are developed to study the dynamics of tensegrity-membrane systems. Two mathematical models are developed based on the nonlinear finite element method. The other model is a control-oriented model, which is suitable for control design. Numerical analysis is conducted using these three models to study the mechanical properties of tensegrity-membrane systems. Two control strategies are developed to regulate the deployment process of tensegrity-membrane systems. The first control strategy is to deploy the system by a nonlinear adaptive controller and use a linear H∞ controller for rapid system stabilization. The second control strategy is to regulate the dynamics of tensegrity-membrane systems using a linear parameter-varying (LPV) controller during system deployment. A gridding method is employed to discretize the system operational region in order to carry out the LPV control synthesis. / Ph. D.

As the load on the power system grows and new transmission facilities become increasingly difficult to build, the utilities must look to ways to make the most of the current transmission system. Adaptive relaying is one way to enhance the ability of the power system. On the Florida - Georgia interface an adaptive out-of-step relay is being installed. This relay determines if swings on the power system will remain stable by performing a better then real-time transient stability study. Because of the computing capacity required for a transient stability study, the study cannot be performed on the full power system. A reduced model must be used. In this thesis, various methods of obtaining reduced models for use in the relay will be explored. The models will be verified with a full system model using Electric Power Research Institute's (EPRI) Extended Transient-Midterm Stability Package (ETMSP). / Master of Science

The motivation of this thesis is to propose a robust control technique for a laser beam system with target estimation. The laser beam is meant to track and fall on a particular portion of the target until the operation is accomplished. There are many applications of such a system. For example, laser range finder uses laser beam to determine the distance of the target from the source. Recently, unmanned aerial drones have been developed that run on laser power. Drone batteries can be recharged with power sup-ply from laser source on the ground. Laser is also used in high energy laser weapon for defence applications. However, laser beams travelling long distances deviate from the desired location on the target due to continually changing atmospheric parameters (jitter effect) such as pressure, temperature, humidity and wind speed. This deviation error is controlled precisely using a lightweight fast steering mirror (FSM) for fine correction. Furthermore, for a moving target, minimizing the deviation of the beam is not sufficient. Hence, in coarse correction, the target has to be tracked by determining its position and assigning the corresponding azimuth and elevation angles to the laser sources. Once these firing angles are settled within an accuracy of +3 mrad, the effort for minimizing the beam deviation (fine correction) takes place to improve the accu-racy to +10 rad. The beam deviation due to jitter effect is measured by a narrow field of view (NFOV) camera at a high frame rate (1000 frames per second), which takes one frame to com-pute this error information. As a result, controller receives error information witha delay from NFOV. This data cannot be modelled for prediction and hence, a few promising data driven techniques have been implemented for one step ahead prediction of the beam deviation. The predictions are performed over a set of sliding window data online after rejecting the outliers through least square approximated straight line. In time domain, methods like auto-regressive least square, polynomial extrapolation (zeroth, first and second order), Chebyshev polynomial extrapolation, spline curve extrapolation are implemented. Further, a convex combination of zeroth order hold and spline extrapolation is implemented. In frequency domain, Fourier series-Fourier transform and L-point Discrete Fourier Transform stretching are implemented where the frequency component of the signal are analysed properly and propagated for one step ahead prediction. After one step ahead prediction, three nominal controllers (PID, DI and DLQR) are designed such that the output of FSM tracks the predicted beam deviation and the performances of these controllers are compared. Since the FSM is excited by high frequency signals, its performance degrades, which leads to parameter degradation in the mathematical model. Hence, three adaptive controllers have been implemented, namely, model reference adaptive control (MRAC), model reference adaptive sliding mode control (MRASMC) and model following neuro-adaptive control (MFNAC). The parameters of the FSM model are degraded up to 20% and the model is augmented with cross coupling terms because the same mirror is used for horizontal and vertical beam deviation. With this condition, the tracking performance and control rate energy consumption of the implemented adaptive controllers are analysed to choose the best among them. For a moving target, in coarse correction, two tracking radars are placed to measure the position of the target. However, this information is assumed to be noisy, for which an extended Kalman filter is implemented. Once the position of the target is known, the desired firing angles of the laser sources are determined. Given the laser source steering mathematical model, a controller is designed such that it tracks the desired firing angle. Once the residual error of the coarse correction settles inside 3 mrad, fine correction takes part to reduce the residual error to 10 rad. The residual error magnitude of the proposed mechanization was analysed for a moving target by perturbing the FSM model by 20% and zeroth order hold predictor with different combinations of angle tolerance and frame tolerance.