No description available.

An alternative to the existing technique of controlling induction machines - vector control - was investigated. In the new technique, sensorless nonlinear control, the mathematical model of the machine was transformed to a linear form and those states which were not measured (sensed) were reconstructed. It was shown possible to maintain stability despite the errors which the use of observers introduces into the control loop. The investigation is founded primarily on a study of the theory. Demonstration of the proposed scheme has been done mainly by means of simulation. The stability of the computer code for simulation was verified by a study of the stiffness and modes (eigenvalues) of the overall system. Furthermore, modifications to the simulation such as the introduction of noise, were made to increase its validity. The main findings were as follows: 1. In the new technique the decoupling of the speed (torque) and flux control is perfect. 2. The linearised model separates into two subsystems, one mechanical and one electromagnetic. 3. The control scheme is robust against disturbances (step change of load). 4. An asymptotic observer can successfully reconstruct both flux and speed states when the whole system is under the linearisation approach. Therefore sensorless nonlinear control is made possible and effective. 5. By selecting initial value(s) for the estimated state(s) close to the command(s) the transient demand on the power supply is reduced. Thus it may be possible to use smaller and cheaper power converters in a drive system. 6. This technique is also able to counteract some of the model uncertainties resulting from temperature variations. The significance of these findings is as follows: 1. Maximum torque and efficiency are achievable only by the new technique. In contrast, in field-weakening under vector control a near optimum is achievable only at the price of degrading the transient behaviour. 2. Direct measurement of flux and speed is avoided, which has, in practice economic benefit. 3. Although the proposed control technique is more complex than field-oriented control, its stability has been analytically proven and, in addition, the rate of convergence (for both the control and the estimator) is adjustable. 4. A sensitivity investigation shows the robustness of the proposed method when the most critical parameter i.e. the rotor resistance, varies slightly from its nominal value. 5. The simulation approach was developed to the point where it was believed possible to investigate the capability of the proposed technique and to identify potential practical problems with the nonlinear control strategy. Moreover the same code can easily be modified for compiling into a microprocessor, so allowing easy implementation of the scheme. 6.The proposed control is easily implementable in commercial drives due to the modest voltage and current demand, even in the initial transient.

The present work introduces the dynamic induction machine model using the concept of space vector notation, and shows the fundamentals of torque production to be related to the current and flux space vector interaction. By theoretical analysis the transient response of the current and voltage fed machine is determined in terms of the machine eigenvalues, and this is confirmed using simulation techniques. The concept of torque control using the current and flux space vectors' magnitude and phase is introduced. It is shown that maintaining the flux space vector's magnitude constant is a sensible approach and that transient free torque responses are possible by controlling the current space vector magnitude and phase with respect to the flux space vector, which is termed vector control. Previously only magnitude control was realised, and this is termed scalar control. It is shown that the simplest practical vector controllers work in the rotating rotor flux space vector reference frame, generated from a dynamic machine model using current and speed/position measurements from the real machine. The major disadvantage of the parameter sensitivity of this approach is examined. To complement the theoretical analysis a practical vector controller was to be built. This was designed around a new DSP micro-controller (TMS320C14) and featured a 10 kHz sampling rate. A fully instrumented 7.5 kW test rig was also developed with the induction machine driven from a modified 1 kHz inverter. The measurement of high performance shaft torque is investigated, to allow comparisons between the theoretical and practical results. The practical work centred on the comparison of the dynamic machine model with measurements made on the real machine (torque and flux) and with the theory. These showed excellent steady state performance but the dynamic response was disappointing. The implications of the model not representing the real machine transiently are investigated.

A new method for solving Hinfinity control problems is developed. The method makes use of the Youla parametrization to characterize the set of all stabilizing controllers K(s) in terms of a stable function Q(s). and also to transform the Hinfinity control problem into a model-matching problem with an objective function E(s) being linear in Q(s). The model-matching problem is then solved by using the interpolation results of Hung. In the general case (i.e. problems of the 3rd kind) closed-form state-space characterizations of optimal and suboptimal solutions for Q(s) and E(s) are given. Furthermore, the solutions generally only require to solve two standard algebraic Riccati equations of smaller size than the McMillan degree of the (generalized) plant. This has an advantage of alleviating the computation burden associated with the ?-iteration required for determining the attainable minimum of ||E(s)||[infinity]. The Hinfinity approach to feedback design with multiple objective functions is studied in this thesis. For a system with two objective functions T[i](s), (i = 1, 2) a design criterion of minimizing the function max (||T[1](s)||[infinity], ||T[2](s)||[infinity]) subject to internal stability of the closed-loop system is proposed. The problem is formulated as an Hinfinity control problem and an iterative algorithm for obtaining a solution is given. A numerical example is given to illustrate the effectiveness of the proposed design technique for tightly bounding and shaping the frequency responses of two objective functions. The application of Hinfinity feedback design techniques to the control of flexible structures is investigated. Experiments are conducted in order to evaluate the use of the Hinfinity approach to the control of flexible structures. An Hinfinity optimal controller is designed and implemented in a laboratory system to manoeuvre a cantilever flexible beam and simultaneously control its vibrations. The controller performance is then assessed. The results obtained are shown to be satisfactory and encouraging.

Many classical control methods are based upon assumptions of linearity and stationarity of the process to be controlled. For the case of motion control of a land vehicle in an unstructured outdoor environment these assumptions do not hold, due to complex vehicle interactions with its surroundings and time--varying environmental conditions. The large number of possible future platforms leads to the desire to produce motion controllers which are generally applicable to a wide range of vehicles with little a priori knowledge of vehicle dynamics. Intelligent, self--learning, systems promise many of the desired features for such controllers. This thesis investigates the use of intelligent controllers for autonomous land vehicle motion control. A new class of fuzzy controller, the indirect adaptive fuzzy controller is proposed as a possible solution to this problem. This controller is then developed by combining on--line adaptive modelling with model causality inversion and on--line controller design. The resulting controller is an analogue of the indirect adaptive algebraic controller. A major advantages of this method is the separation of model convergence and control loops enabling the two aspects to be analysed separately. Demonstration of this work has been achieved by a series of simulation tests using a variety of vehicle models. A conventional front wheel steer road vehicle model has been used as well as two IFAC benchmark control problems (ship autopilot and passenger bus) to investigate the properties of the controller. To test the controller with realistic demand signals, a static rule-based piloting system has also been developed. These simulations have demonstrated i) the successful control of systems with little a priori vehicle knowledge ii) ability to adapt to continuous and sudden parametric changes in the process iii) good noise rejection properties iv) good disturbance rejection properties and v) ability to adapt to stationary loop non--linearities.

No description available.

No description available.

No description available.

Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009 / This project was started as a result of strict environmental and health regulations together with a demand tor cost effective operation of wastewater treatment plants (VVWTPs). The main aim of this project is how to keep effluent concentration below a prescribed limit at the lowest possible cost. Due to large fluctuations in the quality and quantity of the influent concentrations, traditional control methods are not adequate to achieve this aim The major drawback with these methods is that the disturbances affect the process before the controller has time to correct the error (Olsson and Newell, 1999: 454). This problem is addressed through the use of modern control systems. Modern control systems are model based predictive algorithms arranged as feed-forward controllers (Olsson and Newell. 1999: 454). Normally a controller is equipped with a constant set point; the goal In this project is to calculate an optimal DO trajectory that may be sampled to provide a varying optimal set-point for the Activated Sludge Process, In this project an optimal control problem Is formulated using DO concentration as a control variable. This requires a model of the process to be controlled a mathematical expressions of the limitations on the process input and output variables and finally the objective functional. which consists of the objectives of the control. The structures of the Benchmark plant (developed within the COST 682 working group) and the Athlone WWTPs are used to implement this opt.mat control strategy in MATLAB. The plant's full models are developed based on the mass balance principle incorporating the activated sludge biological models: ,ASM1, ASM2, ASM2d and ASM3 (developed by the IWA working groups). To be able to develop a method that may later on be used for online control, the full models are reduced based on the technique In Lukasse (1996). To ensure that the reduced models keep the same prediction capabilities as the full models, parameters of the reduced models are calculated based on the Least Squares principle, The formulated optimal control problem is solved based on the decompostion-coorcdination method that involves time decomposition in a two layer structure. MATLAB software [5 developed to solve the problems for parameter estimation. fun and reduced mode! simulation. and optimal control calculation for the considered different cases of plant structures and biological models. The obtained optimal 00 trajectories produced the effluent state trajectories within prescribed requirements. These DO trajectories may be implemented in different SCADA systems to be tracked as set points or desired trajectories by different types of controllers.

Thesis submitted in fulfilment of the requirements for the degree Master of Technology: Electrical Engineering in the Faculty of Engineering at the Cape Peninsula University of Technology / In the past decade, the need for flexibility and reconfigurability in automation has contributed to the rise of the distributed concept in control systems engineering. The IEC 61499 standard is used to define a distributed model for dividing various components of an industrial application in automation process and complicated control of machinery into function blocks. Such function blocks have the flexibility to be distributed and interconnected across a number of controllers. However, this new standard for automation faces two main challenges: the complexity in designs of distributed systems and the lack of utilization of the standard in industry. Most applications of controllers based on functional block programming are for linear systems. As most of industrial processes are nonlinear there is a need to extend the functional block approach for implementation of nonlinear controllers. Design complexity involves the exact modeling of the system in function blocks to obtain its accurate behaviour and the lack of utilization of the standard is understandable because new technologies are not easily accepted in industry due to their high prices and risks of compromising the performance at the production level. The thesis describes a methodology for design and implementation of nonlinear controllers for nonlinear plants in IEC 61499 standard compliant real-time environment of TwinCAT 3 and Beckhoff Programmable Logic Controller (PLC). The first step is to design the nonlinear controllers and simulate the closed-loop system in MATLAB/SIMULINK software. Then the new engineering based concepts to transform the obtained closed-loop system model to an IEC 61499 Function Block Model. This is accomplished by applying one method which involves a complete model transformation between two block-diagram languages: Simulink and TwinCAT 3. The development tools that support the transformation algorithm in the thesis sets the foundation stone of the verification and validation structure for IEC 61499 function blocks approach. The transformed model of the closed-loop system is downloaded to the Beckhoff PLC and is simulated in real-time. The obtained results demonstrate that the developed methodology allows complex nonlinear controllers to be successfully transformed to IEC 61499 standard compliant environment and to be applied for real-time PLC control of complex plants.