Since uncertainty exists inevitably in control systems, it is questionable whether the controller, designed to compensate a nominal plant well, still guarantees the criteria of robust stability and robust H¡Û performance for the perturbed plant. In this thesis, controller parameters tuning based on the sensitivity concept of structured singular value, called £g-sensitivity, will be adopted to do the parameter adjustment so that, when the influence of uncertainty is considered, the robust stability and robust performance properties of the nominal closed-loop system will be preserved. In view of the time consuming effect of numerical computation and the misjudgment due to discontinuity problem involved in the £g-sensitivity analysis, this thesis proposes the sensitivity concept of skewed structured singular value, called £h-sensitivity, to remedy these drawbacks. Finally, the feasibility of the £h-sensitivity based controller parameters tuning technique is verified by the simulation results of two examples.

A hard chromium electroplating process is normally used for preventing mechanical and electrical parts such as roller, piston and mold from the harmful environments and giving the good physical properties on the surface such as increased wear resistance, increased hardness, low frictional coefficient as well as good aesthetic look on the surface of workpieces. The problem that often found in this process is the deflected workpieces after plating process due to the low plating performance during a plating period. These deflected workpieces are needed to replating it again. However, the replating method causes a large amount of resource consumptions and increases the production time. To handle this problem, the plating solution temperature is needed to maintain the plating solution temperature at a set point about 50 °C in order to improve the plating performance during the plating period and decrease the occurrence of the deflected workpieces. In this work, the mathematical models are developed to explain the dynamic behavior of the plating solution temperature during the plating time and validated with the real data from a plant. The conventional (PID) controller is applied to this process for the purpose of keeping the plating solution temperature at the set point throughout the plating time. The result demonstrates that the developed mathematical models can be used to explain the dynamic behavior of the plating solution temperature because it gives the good simulation of the plating solution temperature with a slightly different from the real data. Furthermore, the PID controller shows the high control performance for maintaining the plating solution temperature at the set point throughout the plating period with small overshoot at the beginning of every batch.

Maintaining the pH of a fluid or a solution at a specific value is a concern in many industrial processes, wastewater management, and food and pharmaceutical production. Given the importance of controlling pH in many processes, the objective of this thesis is to study and compare the effectiveness of some controller algorithms to control the pH of a process. In this study, the performance of three controller algorithms, namely PID, fractional PID and LA controllers, is evaluated for the control of a simple neutralization process using conventional controller performance metrics. Performance metrics used are the response time, the Integral of the Time weighted Absolute Error (ITAE), the Integral of the Squared Error (ISE), and the Integral of the Squares of the changes (ΔU) in the manipulated variable (ISDU). The three controllers were therefore tuned to minimize one or a combination of the controller performance metrics. Results show that PID, fractional PID and LA controllers implemented and tested in this research are all worthy controllers for maintaining pH of the neutralization process. Simulation results show that the three controllers can be used with confidence to cope with the high nonlinearity of a pH neutralization process provided that the process is properly designed. The relative small gain in performance obtained with the fractional PID controller, compared to a linear PID controller, suggests that it is not worth resorting to a fractional PID controller given its complexity and higher computation effort. Results show that PID and LA controllers are easy to implement with short response time and low ITAE and ISDU performance metrics.

<p>To fulfill todays requirements on emissions from engines, SCANIA has developed an engine with EGR (Exhaust Gas Recirculation) and VGT (Variable Geometry Turbine). This gives two extra control signals to take into consideration. Open loop optimal control is used to investigate how these two actuators should be controlled to minimize emissions and fuel consumption. A cost function, consisting of the errors between the most important variables and their set points, has been used in the minimization. The variables are the torque, the EGR mass fraction, the oxygen/fuel ratio and the pumping losses.</p><p>From studies of the two control signals in different transients in the engine, information of how to control the VGT and EGR in the optimal way is found. The result from the optimal control has been compared with a PID simulation and has showed a better way to control the signals. The mayor reason why the optimal control is better than a PID controller is the ability to use future values from the transients.</p>

This report presents a new way of control engineering. Dc motor speed controlled by three controllers PID, pole placement and Fuzzy controller and discusses the advantages and disadvantages of each controller for different conditions under loaded and unloaded scenarios using software Matlab. The brushless series wound Dc motor is very popular in industrial application and control systems because of the high torque density, high efficiency and small size. First suitable equations are developed for DC motor. PID controller is developed and tuned in order to get faster step response. The simulation results of PID controller provide very good results and the controller is further tuned in order to decrease its overshoot error which is common in PID controllers. Further it is purposed that in industrial environment these controllers are better than others controllers as PID controllers are easy to tuned and cheap. Pole placement controller is the best example of control engineering. An addition of integrator reduced the noise disturbances in pole placement controller and this makes it a good choice for industrial applications. The fuzzy controller is introduce with a DC chopper to make the DC motor speed control smooth and almost no steady state error is observed. Another advantage is achieved in fuzzy controller that the simulations of three different controllers are compared and concluded from the results that Fuzzy controller outperforms to PID controller in terms of steady state error and smooth step response. While Pole placement controller have no comparison in terms of controls because designer can change the step response according to nature of control systems, so this controller provide wide range of control over a system. Poles location change the step response in a sense that if poles are near to origin then step response of motor is fast. Finally a GUI of these three controllers are developed which allow the user to select any controller and change its parameters according to the situation.

A common configuration in buses is that the engine is placed in the rear of the bus and that the batteries are placed in thefront of the bus due to optimization of the distribution of the weight. The long wires running between the engine and the batteries together with large power consuming units, such as fans and air condition units, result in voltage drops. The voltage drops contribute to the battery charging voltage level being lower than desired. The aim with this thesis work is to implement a control system that increases the battery voltage level when the voltage drops occur. Measurements are performed on an articulated bus that is in focus throughout the whole thesis work. A model for the electrical circuit of the bus is created and used when investigating the stability of the control system. The control system isimplemented in the bus, where also verification tests are performed. The verification tests confirm that the control system raises the battery charging voltage to the desired level. The increased voltage level makes the batteries reach a higher state of charge in shorter time since the control system provides the batteries with more charge.

To fulfill todays requirements on emissions from engines, SCANIA has developed an engine with EGR (Exhaust Gas Recirculation) and VGT (Variable Geometry Turbine). This gives two extra control signals to take into consideration. Open loop optimal control is used to investigate how these two actuators should be controlled to minimize emissions and fuel consumption. A cost function, consisting of the errors between the most important variables and their set points, has been used in the minimization. The variables are the torque, the EGR mass fraction, the oxygen/fuel ratio and the pumping losses. From studies of the two control signals in different transients in the engine, information of how to control the VGT and EGR in the optimal way is found. The result from the optimal control has been compared with a PID simulation and has showed a better way to control the signals. The mayor reason why the optimal control is better than a PID controller is the ability to use future values from the transients.

Magnetic suspension systems are highly nonlinear and essentially unstable systems. In this thesis, we utilize a phase-lead controller operating in the inner loop to stabilize the magnetic suspension system at first. Furthermore, we design a fuzzy PID controller operating in the outer loop to overcome the nonlinearity and to improve the system¡¦s performances. Because of setting the parameters in traditional fuzzy PID is a long-winded trial and error, so we adopt non-binary modified adaptive genetic algorithms to help us finding the parameters of fuzzy PID controller. As to the experimental implementation, we set two situations in our experiment test: (1) we utilize fuzzy PID controller with initial voltage to test the positions control, and eliminate the extra disturbance. And, (2) we utilize fuzzy PID controller without initial voltage to control the position of suspension object. For the experimental results, we obtain that the designed fuzzy PID controller not only increases the system¡¦s operating range, but also positions accurately and rapidly, and it meanwhile can eliminate the extra disturbance.

ABSTRACT In this dissertation, several adaptive control design schemes for a class of nonlinear systems are proposed. The first topic of the research is concerned with self-tuning PID controller design. The main problem of designing PID controller is how to determine the values of three control gains, i.e., proportional gain , integral gain , and derivative gain . We attempt to use the technique of adaptive control based on the Lyapunov approach to design the PID controller for some class of partially known nonlinear systems. Three PID control gains are adjusted on-line such that better output performance can be achieved. The stability of the closed-loop PID control systems is analyzed and guaranteed by introducing a supervisory control and a modified adaptation law with projection. Second, two kinds of adaptive neural control systems including the direct and indirect neural controls are considered by using simple single auto-tuning neuron. We will first propose a novel neuron called auto-tuning neuron and use it to take place of the roles of the traditional neural networks used in the direct and indirect adaptive neural control systems. This can greatly reduce the computational time and network complexities due to the simple configuration of the auto-tuning neuron. It is also easy for hardware implementation. Third, based on the idea borrowed from natural evolution, genetic algorithm can search for optimal or near-optimal solutions for an optimization problem over the search domain. An optimization technique of real-coded genetic algorithm is used to design the PID controller by minimizing the performance index of integrated absolute error. The improvements of our results over that using other methods are also illustrated. In the last part of each section, some computer simulation results will also be provided to illustrate our proposed methods.

In position control systems like linear motor, friction is a key factor to influence the control performance when micron or sub-micron meter accuracy is required. To overcome the effect of the friction, besides a general model of the linear motor system, past researches have shown an additional static friction model of the system is necessary for a better control performance when the motor move into the micro region of the system (usually <100£gm). Two models, macro and micro model of the system have been well constructed by two different identification methods. After model construction, two different controllers are also designed for each model. A traditional pole-placement PID controller can be easily obtained for the macro model to move into the micro region quickly and stably. Then in micro model design, from the experiments, it is found that system parameter varies and thus degrades the positioning performance of the system. So, a Sliding-Mode Controller is designed to improve these problems. With a two step control strategy, macro and micro step, the linear motor positioning system can achieve a 0.1£gm accuracy within 0.2 sec.