Gaseous exhaust of different industries contains dust particles of different chemical precipitates that are harmful for the environment. Electrostatic Precipitators are very often used in industries to filter their gaseous exhaust and to prevent the atmosphere to being polluted. Electrostatic Precipitators are very efficient in their work. Electrostatic Precipitators use the force of the electric field to separate the dust particles from gaseous exhaust. Electrostatic Precipitators charge the dust particles and remove these particles by attracting these charged dust particles toward the collecting plates. The charging of dust particles requires a charging zone. When gas passes through that charging zone, the dust particles in the gas stream become charged and then these charged particles are attracted toward the collecting plates. The design of an Electrostatic Precipitators requires the knowledge of its working principle and the problems that often arise during its working. This thesis is the study of the working and the problems of the Electrostatic Precipitators. The main reason for problems in working of an Electrostatic Precipitator is the dust resistivity. This dust resistivity affects the collection performance of an Electrostatic Precipitator. This thesis also contains the simulation of an Electrostatic Precipitator. In the simulation part, the Electric Potential and the Electric Field of an ESP is modeled in an ideal condition, when no gas is flowing through the ESP. The industrial software Comsol Multiphysics is used for the simulation. A Comsol Multiphysics guide is given in appendix of this thesis report that provides information about using this software.

A turbo system is driven by the excess energy in the exhaust gases.  As a result, variation in exhaust temperature cause variations in  boost pressure. By using the information about the available exhaust  energy in the turbo controller directly through a feedforward  controller, an unexpected variation in turbo boost can be avoided. A  model based controller is developed that calculates the desired  turbine power from the boost pressure reference and then, by  observing the available exhaust energy, controls the generated  turbine power to match the desired power. A Mean Value Engine Model  has been used to make simulation with the developed controller  implemented. Steps between different boost pressure references are  used to evaluate controller performance. Tests in a car have also  been made to make sure the simulation results are consistent in a  real environment. / Turbosystem drivs av överskottsenergin i motorns avgaser. Dettainnebär att temperaturvariationer i avgaserna orsakar variationer igenererad turbineffekt och därmed ökat laddtryck från turbosystemet.Används informationen om den tillgängliga energin i avgaserna när manstyr turbinen så kan man motverka oväntade laddtrycksförändringar. Idenna rapport har en modellbaserad turboregulator med en framkopplingsom beräknar en önskad turbineffekt från givet referenstryckutvecklats. Sedan tas en styrsignal fram till turbinen som, genom attanvända informationen om den observerade energin i avgaserna, matcharden önskade turbineffekten. En model av en medelvärdesmotor haranvänds för att validera prestandan i regulatorn via stegsvar mellanolika referenstryck. Det har även utförts tester i bil för att avgöraom resultatet blir detsamma under verkliga förhållanden.

The aim of this work is to evaluate the fuzzy system for different types of patients for levodopa infusion in Parkinson Disease based on simulation experiments using the pharmacokinetic-pharmacodynamic model. Fuzzy system is to control patient’s condition by adjusting the value of flow rate, and it must be effective on three types of patients, there are three different types of patients, including sensitive, typical and tolerant patient; the sensitive patients are very sensitive to drug dosage, but the tolerant patients are resistant to drug dose, so it is important for controller to deal with dose increment and decrement to adapt different types of patients, such as sensitive and tolerant patients. Using the fuzzy system, three different types of patients can get useful control for simulating medication treatment, and controller will get good effect for patients, when the initial flow rate of infusion is in the small range of the approximate optimal value for the current patient’ type.

This thesis was done at DaimlerChrysler AG in Stuttgart,Germany. The aim of the thesis is to develop an algorithm for controlling a motor used in a Shift-by-Wire System. The control algorithm is to be implemented in a prototype car for further testing. The Shift-by-Wire System can be described as follows: An electrical actuator is mounted in an automatic gearbox to select gears instead of the gear stick. The actuator is controlled by a microcontroller, which runs a control algorithm. The position of the actuator is measured with a linear position sensor and sent to the controller.

Automation in manufacturing has come far by using industrial robots. However, industrial robots require tremendous efforts in static calibration due to their lack of senses. Force and vision are the most useful sensing capabilities for a robot system operating in an unknown or uncalibrated environment [4]and by integrating sensors in real-time with industrial robot controllers, dynamic processes need far less calibration which leads to reduced lead time. By using robot systems which are more dynamic and can perform complex tasks with simple instructions, the production efficiency will rise and hence also the profit for companies using them. Although much research has been presented within the research community, current industrial robot systems have very limited support for external sensor feedback, and the state-of-the-art robots today have generally no feedback loop that can handle external force- or position controlled feedback. Where it exists, feedback at the rate of 10 Hz is considered to berare and is far from real-time control. A new system where the feedback control can be possible within a real-time behavior, developed at Lund Institute of Technology, has been implemented and deployed at Linköping Institute of Technology. The new system for rapid feedback control is a highly complex system, possible to install in existing robot cells, and enables real-time (250 Hz) sensor feedback to the robot controller. However, the system is not yet fully developed, and a lot of issues need to be considered before it can reach the market in other than specific applications. The implementation and deployment of the new interface at LiTH shows that the potential for this system is large, since it makes production with robots exceedingly flexible and dynamic, and the fact that the system works with real- time feedback makes industrial robots more useful in tasks for manufacturing.

The longitudinal controller at DaimlerChrysler AG consists of two cascade controllers. The outer control loop contains the driver assistance functions such as speed limiter, cruise control, etc. The inner control loop consists of a PID-controller and an observer. The task of the observer is to estimate the part of the vehicle's acceleration caused by large disturbances, for example by a changed vehicle mass or the slope of the road. As observer the Kalman filter is selected. It is the optimal filter when the process model is linear and the process noise and measurement noise can be modeled as Gaussian noise. In this Master's thesis the theory for the Kalman filter is presented and it is shown how to choose the filter parameters. Simulated annealing is a global optimization technique which can be used when autotuning, i.e., automatically find the optimal parameter settings. To be able to perform autotuning for the longitudinal controller one has to model the environment and driving situations. In this Master's thesis it is verified that the parameter choice is a compromise between a fast but jerky, or a slow but smooth estimate. As the output from the Kalman filter is directly added to the control value for the engine and brakes, it is important that the output is smooth. It is shown that the Kalman filter implemented in the test vehicles today can be exchanged with a first-order lag function, without loss in performance. This makes the filter tuning easier, as there is only one parameter to choose. Change detection is a method that can be used to detect large changes in the signal, and react accordingly - for example by making the filter faster. A filter using change detection is implemented and simulations show that it is possible to improve the estimate using this method. It is suggested to implement the change detection algorithm in a test vehicle and evaluate it further.

This work made publicly available electronically on July 7, 2011.This thesis developed a new practical tuning method for fractional order proportional and integral controllers (FO-PI / PI®) for varying time-delay systems like networked con- trol systems (NCS), sensor networks, etc. Based on previously proposed FO-PI controller tuning rules using fractional Ms constrained integral gain optimization (F-MIGO), simulta- neous maximization of the jitter margin and integrated time weighted absolute error (ITAE) performance for a set of hundred gain delay time-constant (KLT) systems having di®erent time-constants and time-delay values are achieved. A multi-objective optimization algo- rithm is used to simultaneously maximize the ITAE factor and jitter margin of the plants at initial F-MIGO gain parameters. The new values of controller gain parameters are gen- eralized to give a new set of optimal fractional order proportional integral (OFOPI) tuning rules such that the jitter margin and system performance of closed-loop KLT systems are maximized and yet the closed-loop feedback system is stable. This is further tested and veri¯ed by simulation techniques. Comparisons are made with other existing proportional integral derivative (PID) and fractional order proportional integral (PI) tuning rules to prove the e±ciency of the new technique. It is further shown that OFOPI tuning rules per- form better than traditional tuning methods for lag-dominated FOPDT systems, because it can take the varying time-delay better into account. The tuning method is modi¯ed to work with discrete-time controllers in the context of NCSs. Furthermore, experimental results in a NCS platform, Stand-alone Smart Wheel (omnidirectional networked control robot wheel), are reported using the tuning rules developed in this thesis. The optimization tuning method performed almost equally well in practice as in simulations. The thesis also shows that the tuning rule development procedure for OFOPI is not only valid for FOPDT systems but is also applicable for other general classes of plants which could be reduced to ¯rst order plant systems. Temperature control in heat °ow apparatus and water-level control in a coupled tank system using FO-PI tuning rules are other major contributions of this thesis work.

In this thesis, a grid-connected wind-energy converter system including a matrix converter is proposed. The matrix converter, as a power electronic converter, is used to interface the induction generator with the grid and control the wind turbine shaft speed. At a given wind velocity, the mechanical power available from a wind turbine is a function of its shaft speed. Through the matrix converter, the terminal voltage and frequency of the induction generator is controlled, based on a constant V/f strategy, to adjust the turbine shaft speed and accordingly, control the active power injected into the grid to track maximum power for all wind velocities. The power factor at the interface with the grid is also controlled by the matrix converter to either ensure purely active power injection into the grid for optimal utilization of the installed wind turbine capacity or assist in regulation of voltage at the point of connection. Furthermore, the reactive power requirements of the induction generator are satisfied by the matrix converter to avoid use of self-excitation capacitors. The thesis addresses two dynamic models: a comprehensive dynamic model for a matrix converter and an overall dynamical model for the proposed wind turbine system. The developed matrix converter dynamic model is valid for both steady-state and transient analyses, and includes all required functions, i.e., control of the output voltage, output frequency, and input displacement power factor. The model is in the qdo reference frame for the matrix converter input and output voltage and current fundamental components. The validity of this model is confirmed by comparing the results obtained from the developed model and a simplified fundamental-frequency equivalent circuit-based model. In developing the overall dynamic model of the proposed wind turbine system, individual models of the mechanical aerodynamic conversion, drive train, matrix converter, and squirrel-cage induction generator are developed and combined to enable steady-state and transient simulations of the overall system. In addition, the constraint constant V/f strategy is included in the final dynamic model. The model is intended to be useful for controller design purposes. The dynamic behavior of the model is investigated by simulating the response of the overall model to step changes in selected input variables. Moreover, a linearized model of the system is developed at a typical operating point, and stability, controllability, and observability of the system are investigated. Two control design methods are adopted for the design of the closed-loop controller: a state-feedback controller and an output feedback controller. The state-feedback controller is designed based on the Linear Quadratic method. An observer block is used to estimate the states in the state-feedback controller. Two other controllers based on transfer-function techniques and output feedback are developed for the wind turbine system. Finally, a maximum power point tracking method, referred to as mechanical speed-sensorless power signal feedback, is developed for the wind turbine system under study to control the matrix converter control variables in order to capture the maximum wind energy without measuring the wind velocity or the turbine shaft speed.

The main objective of this research is the development of a flexible test-bench for evaluation of hybrid electric powertrain controllers. As a case study, a real-time near-optimal powertrain controller for a series hybrid electric vehicle (HEV) has been designed and tests. The designed controller, like many other optimal controllers, is based on a simple model. This control-oriented model aims to be as simple as possible in order to minimize the controller computational effort. However, a simple model may not be able to capture the vehicle's dynamics accurately, and the designed controller may fail to deliver the anticipated behavior. Therefore, it is crucial that the controller be tested in a realistic environment. To evaluate the performance of the designed model-based controller, it is first applied to a high-fidelity series HEV model that includes physics-based component models and low-level controllers. After successfully passing this model-in-the-loop test, the controller is programmed into a rapid-prototyping controller unit for hardware-in-the-loop simulations. This type of simulation is mostly intended to consider controller computational resources, as well as the communication issues between the controller and the plant (model solver). As the battery pack is one of the most critical components in a hybrid electric powertrain, the component-in-the-loop simulation setup is used to include a physical battery in the simulations in order to further enhance simulation accuracy. Finally, the driver-in-the-loop setup enables us to receive the inputs from a human driver instead of a fixed drive cycle, which allows us to study the effects of the unpredictable driver behavior. The developed powertrain controller itself is a real-time, drive cycle-independent controller for a series HEV, and is designed using a control-oriented model and Pontryagin's Minimum Principle. Like other proposed controllers in the literature, this controller still requires some information about future driving conditions; however, the amount of information is reduced. Although the controller design procedure is based on a series HEV with NiMH battery as the electric energy storage, the same procedure can be used to obtain the supervisory controller for a series HEV with an ultra-capacitor. By testing the designed optimal controller with the prescribed simulation setups, it is shown that the controller can ensure optimal behavior of the powertrain, as the dominant system behavior is very close to what is being predicted by the control-oriented model. It is also shown that the controller is able to handle small uncertainties in the driver behavior.

Shape Memory Alloys (SMAs) have been demonstrated to be effective actuator elements in a wide range of applications, such as robotics, medicine, aerospace and automotive. Enabled by the unique thermo-mechanical properties of SMAs, these actuators offer the advantages of light weight, high power-to-weight ratio and a simple actuation mechanism compared to traditional actuator types. At the same time, the widespread adoption of the SMA actuator remains elusive as its low power efficiency and complex hysteretic behaviour often render it an impractical means of actuation. These actuators also exhibit a slow response speed and their response is highly sensitive to changes in the external environment, namely ambient temperature and mechanical stress, thus complicating their control. Position, force or temperature sensors may be used to facilitate feedback control, but at the cost of increasing the overall size and complexity of the system. The difficulties caused by the hysteretic behaviour can be largely avoided when SMA wires are used as on-off actuators, making SMAs well suited for such applications. However, they may still be subject to a wide range of dynamic operating conditions that would impact their actuation time, and achieving a consistent actuation time is often highly desirable. This thesis presents the synthesis of a nitinol SMA actuator control system which uses electrical resistance feedback to enable a fast response speed and robustness to disturbances in the external environment. A study of the resistance behaviour of SMAs is discussed first. The design of an adaptive controller and the experimental evaluation of its performance are described in detail next. The objective of the SMA actuator control system is to achieve a consistent and fast actuation time throughout the range of operating ambient temperature and stress. The control system is implemented experimentally and shown to be quite successful.