The goal of this thesis has been to create a map of road lanes from piece-wisedetections. Using images from a stereo camera, an existing algorithm is able todetect lane tracks in real-time. With a basis spline (B-spline) representation ofthe tracks, these curve features are converted into point features. These are combinedoff-line with an odometric estimate for the creation of a motion and lanetrack map. Fusion of odometric and feature measurements is done using an optimizationbased simultaneous localization and mapping (slam) method. By use of visual inspection and a differential global positioning system (dgps) theresult is validated. The method is able to improve on existing motion estimatorsby using the curvature of lane tracks. A projection of the resulting map is usedto automatically label lane tracks as seen from camera view with accuracy andrange exceeding that of the real-time algorithm.

This thesis is devoted to the modelling and control of rotary crane systems. The goal is to design a control system that assists the operator to move a cargo without oscillations and to correctly align the cargo at the final position. The control system is divided into two independent parts, one dealing with the alignment of the load with the aid of a power swivel or a cargo rotating device, and a second that deals with the elimination of load oscillations. Both design and implementation of the control algorithms on a full scale crane are considered. In the cargo alignment system a linear cascade controller is considered that is shown to have near time-optimal performance for a system with saturation in both the angle and the angular rate of the power swivel. In the second part a weakly coupled pair of state feedback controllers with a nonlinear compensator is used to eliminate the load oscillations in two dimensions. In the third part of the thesis a software tool for simulation and real time control is presented. The development of the program started as a spin-off to the crane projects. / Godkänd; 1993; 20070417 (tgu)

A time-varying linear system is a realistic description of many industrial processes, and nonlinear behavior can then also be accounted for. Then, we can consider a linear system with time-varying parameters as the model uncertainty, \emph{e.g.} an AR(X) model or an affine input-output approximation. In this thesis, we seek to estimate these parameters of the linear time-varying system for two purposes: 1) As uncertainty bounds for use in robust control. 2) Fault detection and isolation.Robustness is a necessary property of a control system in an industrial environment, due to changes of the process such as changes of material quality, aging of equipment, replacing of instrument, manual operation (\emph{e.g.} a valve that is opened or closed) etc. The uncertainties associated with the nominal process model is a concern in most approaches to robust control. One purpose of this research is to achieve a bound of the uncertainty by using a set of measurement data.Change detection is a quite active field, both in research and applications. Faults occur in almost all systems, and change detection often has the aim to locate the fault occurrence in time and to raise an alarm. Examples of faults in an industry are leakage of a valve, clogging of a valve or faults in measurement instruments. The second purpose of this research is thus to detect faults under the assumption that these are manifested as abrupt parameter changes.Many time-varying changes or faults of industrial processes can be described as abrupt changes in parameters. The approach is to model them as piecewise constant parameters which results a sparse structure of their derivative. This quality serves as a cost and regularization on flexibility for parameter estimation.Sparsity can be approximated in different ways, \emph{e.g.} with $l_q$-norm for $q\leq1$. We present several online methods to estimate piecewise constant parameters, based on these approximators. As an application, the parameters of a pump in the flue gas desulphurization process at the Luossavaara-Kiirunavaara AB (LKAB) facility in Malmberget, Sweden, are estimated for the purpose of detecting if the pump is coated or worn.We also present an exact solution of maximization of sparsity by using MILP (Mixed Integer Linear Programming) to minimize the number of non-zero elements in a matrix or vector. The metod is used as a regularization to estimate the time-varying parameters of an AR(X) model. We specifically apply it to detect faults in a blender's hinged-outflow valve which is included in the pelletization of LKAB. Proper function of this valve is essential for the mixing of bentonite and slurry and thus for the quality of the iron ore pellets. Simulation with measurement data from the LKAB facility at Malmberget, Sweden, shows the viability of the algorithm.We consider a time-varying time-delay first-order process model. The gain, time-constant and time-delay are considered as uncertainties in this example. An estimate of the perturbations is produced based on the MILP method. The Pad\'-approximation and orthogonal collocation method are used to approximate the delay. An overhead crane with uncertain parameters is also used as an illustrative example. / <p>Godkänd; 2011; 20110829 (soheil); DISPUTATION Opponent: Professor Alexander Medvedev, Institutionen för informationsteknologi, Uppsala universitet, Uppsala Ordförande: Professor Thomas Gustafsson, Institutionen för system- och rymdteknik, Luleå tekniska universitet, Luleå Tid: Fredag den 30 september 2011, kl 10.00 Plats: A109, Luleå tekniska universitet</p> / Modellering av komplexa dynamiska system

Stricter legislations on nitrogen removal together with increasing wastewater loads have successively increased the need for optimization and control of activated sludge processes. The aim of this thesis is primarily to propose and illustrate methods for modelling and control of activated sludge processes, and thus possibly improve process efficiency. The first part of this thesis describes a JAVA based simulator of the activated sludge process. Its features are discussed, and some control strategies are illustrated. The second part of the thesis presents a simple model based feedforward controller for controlling the nitrate level by using an external carbon source. Several simulation examples are used to illustrate the control law. In the third part, a model based strategy for control of the ammonium level by manipulating the aeration volume in the activated sludge process is presented. The strategy is based on exact linearization combined with some logical programming rules in order to deal with discrete volume changes. The control law is also evaluated in simulations.

The pole assignment problem has been subject for research for a long time. For single-input single-output systems this problem is well understood but for multi-input multi-output systems the pole assignment problem is more complex. In this thesis a parameterization of state feedback gains for pole assignment is characterized with respect to completeness, redundancy and existence. In order to make a systematic examination of this parameterization a number of classes are introduced. This parameterization depends on two matrices that can be regarded as design parameters. In the thesis it is shown how the degree of freedom in the pole assignment problem for multi-input systems is characterized by these two matrices. It turns out that the properties of the parameterization depends on whether the characteristic polynomials of the open and the closed loop systems are coprime or not. It is shown in the thesis that if the characteristic polynomials are coprime, every possible feedback gain can be parameterized in this way, and in this sense the parameterization is complete. If the characteristic polynomials have factors in common the parameterization is not complete. In the thesis the shortcomings of the parameterization for this case are characterized. The design parameters seem to offer a greater degree of freedom than what can be offered in the pole assignment problem. This indicates a certain degree of overparameterization. This redundancy in the design parameters is characterized in the thesis. The parameterization implies that a certain matrix is invertible. Necessary conditions for when this matrix is invertible are given in terms of the two design parameters. It is shown that this matrix is invertible for almost every value of the design parameters when the characteristic polynomials are coprime, and hence that the parameterized gains are generally applicable. The parameterization and its properties are illustrated on a linear model of the military aircraft JAS Gripen.

During the last few decades, wastewater treatment processes in urban water management have become more and more efficient and complex. Several factors such as urbanization, stricter legislations on effluent quality, economics, increased knowledge of the involved biological, chemical and physical processes as well as technical achievements have been important incentives for the development of more efficient procedures for wastewater treatment plants. Future requirements on more sustainable urban water systems, in combination with increasing wastewater loads, will most probably further increase the need for optimization and control of both existing and emerging wastewater treatment processes. In this thesis estimation, modelling and control strategies are developed in order to improve the efficiency of the activated sludge process. The first part of the thesis presents a JAVA based simulator of the activated sludge process. An overview of its features, with some emphasis on implemented control strategies, is given. In particular, a new control strategy for the internal recycling flow rate is described. A summary of experiences from using the simulator as a teaching and training tool is also given. The second part of the thesis includes a derivation of reduced order models for the activated sludge process. The resulting models, a time-varying linear state-space model for the anoxic part and a time-varying bilinear state-space model for the aerobic part, are intended to be used for control applications. In the third part, an adaptive control strategy for control of the nitrate level using an external carbon source is presented. The controller adapts and compensates for changes in the system dynamics since important system parameters are estimated adaptively and incorporated on-line in the control design. The estimated system parameters and model states also give guidance about the state of the process and the characteristics of the wastewater. Several simulation examples are used to illustrate the control law. Finally, a new suboptimal control law for the bilinear quadratic regulator problem with infinite final time is presented. The control strategy is evaluated in a simulation study, where special concern is devoted to controlling the activated sludge process, using the bilinear model developed in the second part of this thesis.

All mechanical systems exhibit vibrational response when exposed to external disturbances. In many engineering applications vibrations are undesirable and may even have harmful effects. Therefore, control of mechanical vibration is an important topic and extensive research has been going on in the field over the years. In active control of vibration, the ability to actuate the system in a controlled manner is incorporated into the structure. Sensors are used to measure the vibrations and secondary inputs to the system are used to actuate the flexible body in order to obtain some desired structural response. In this thesis, feedback and feedforward control of active structures are addressed. The thesis is divided into four parts. The first part contains a general introduction to the subject of active vibration control and also provides an outline of the thesis. The second part of the thesis treats modeling and feedback control of a beam system with strain sensors and piezoelectric actuators. Physical modeling and system identification techniques are utilized in order to obtain a low order parametric model that is suitable for controller design. The third part introduces the concept of a mechanical wave diode, which is based on feedforward control. A controller is derived on the basis of equations that describe elastic waves in bars. The obtained controller is shown to have poor noise properties and is therefore modified and further analyzed. The final part of the thesis treats the same type of wave diode system as part three, but with more general feedforward filters. Especially, a controller based on Wiener filter theory is derived and shown to drastically improve the performance of the mechanical wave diode.

Efficient control of wastewater treatment processes are of great importance. The requirements on the treated water (effluent standards) have to be met at a feasible cost. This motivates the use of advanced control strategies. In this thesis the activated sludge process, commonly found in the biological wastewater treatment step for nitrogen removal, was considered. Multivariable interactions present in this process were analysed. Furthermore, control strategies were suggested and tested in simulation studies. The relative gain array (RGA), Gramian based interaction measures and an interaction measure based on the H2 norm were considered and compared. Properties of the H2 norm based measure were derived. It was found that the Gramian based measures, and particularly the H2 norm based measure, in most of the considered cases were able to properly indicate the interactions. The information was used in the design of multivariable controllers. These were found to be less sensitive to disturbances compared to controllers designed on the basis of information from the RGA. The conditions for cost-efficient operation of the activated sludge process were investigated. Different fee functions for the effluent discharges were considered. It was found that the economic difference between operation in optimal and non-optimal set points may be significant even though the treatment performance was the same. This was illustrated graphically in operational maps. Strategies for efficient control were also discussed. Finally, the importance of proper aeration in the activated sludge process was illustrated. Strategies for control of a variable aeration volume were compared. These performed overall well in terms of treatment efficiency, disturbance rejection and process economy.

The complexity of industrial systems and the mathematical models to describe them increases. In many cases point sensors are no longer sufficient to provide controllers and monitoring instruments with the information necessary for operation. The need for other types of information, such as audio and video, has grown. Suitable applications range in a broad spectrum from microelectromechanical systems and bio-medical engineering to papermaking and steel production. This thesis is divided into five parts. First a general introduction to the field of vision-based and sound-based monitoring and control is given. A description of the target application in the steel industry is included. In the second part, a recursive parameter estimation algorithm that does not diverge under lack of excitation is studied. The focus is on the stationary properties of the algorithm and the corresponding Riccati equation. The third part compares the parameter estimation algorithm to a number of well-known estimation techniques, such as the Normalized Least Mean Squares and the Kalman filter. The benchmark for the comparison is an acoustic echo cancellation application. When the input is insufficiently exciting, the studied method performs best of all considered schemes. The fourth part of the thesis concerns an experimental application of vision-based estimation. A water model is used to simulate the behaviour of the steel bath in a Linz–Donawitz steel converter. The water model is captured from the side by a video camera. The images together with a nonlinear model is used to estimate important process parameters, describing the heat and mass transport in the process. The estimation results are compared to those obtained by previous researchers and the suggested approach is shown to decrease the estimation error variance by 50%. The complexity of the parameter estimation procedure by means of optimization makes the computation time large. In the final part, the time consumption of the estimation is decreased by using a smaller number of data points. Three ways of choosing the sampling points are considered. An observer-based approach decreases the computation time significantly, with an acceptable loss of accuracy of the estimates.

The topic for this thesis is the analysis of human movement, or more specifically, markerless analysis of human movement from video material. By markerless analysis is meant that the full image material is used as input in contrast with traditional marker systems that only use the positions of marker centers. The basic idea is to use more of the information in the images to improve the analysis. Starting of with the aim of markerless analysis an application is designed that use, to the subject added texture to estimate the position of the knee joint center in real images. The approach show the plausibility of using subject texture for estimation purposes. Another issue that is addressed is how one can generate synthetic image data. Using basic tools of graphics programming a virtual environment used to synthesize data is created. This environment is also used to evaluate some different camera solutions. One method to make three dimensional reconstruction from multiple images of an object is tested using the synthetic data. The method is based on a "brute force" approach and does not show good performance in terms of computing speed. With appropriate representations of the three dimensional objects, mathematical methods might speed up the analysis.