Faculty of Engineering and Built Environment
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Item Controlling the feedrate of material from a vibratory pipe conveyor using an electro-magnetic vibrator and load cell system(1994) Janse van Vuuren, Gary Peter; Eitelberg, E.This work presents a novel way of controlling the feed rate of raw material from a vibratory pipe feeder system. The system consists of a hopper, feeder pipe, electromechanical vibrator and a loadcell which measures the mass of the complete system. Raw material is gravity fed onto the vibrating pipe whose amplitude of vibration controls the amount of material fed.Item Design of a non-linear analog PID controller(1997) Govender, Poobalan; Bajic, Vladimir B.In this study we propose an analogue nonlinear PID controller with antiwindup and dead-time compensation to optimise the control of loops experiencing degradation in the control performance as a result of dead-time and saturation nonlinearity. Loops containing a significant dead-time are notoriously difficult to control. The proposed controller optimises the control of loops experiencing the negative effects of saturation and dead-time.Item Optimization approach to the frequency design of compensators for nonlinear systems with dead time(1998) Stavrou, Marios; Bajic, Vladimir B.Designing compensators in the frequency domain is a complicated problem even for linear systems that have dead time. The situation is far more difficult if the system is also nonlinear. This study introduces a new method for the design of compensators for time-invariant, nonlinear systems that have dead time. The method is based on an optimization approach and utilizes large signal linearization methodology.Item An investigation into the feasibility of the use of an electrostatic technique for the measurement of mass flow rate of pneumatically conveyed solids(1997) Hole, Evan D.; Bajic, Vladimir B.This report details the findings of work carried out over the course of 1994 and 1995 to determine if it is feasible to use an electrostatic technique for the measurement of mass flow rate of pneumatically conveyed solids. This includes results from tests done on a flow rig and at various power stations.Item Preaging techniques as a means of stabilising thermoelectric drift in nickel-chromium/nickel-aluminium thermocouples for use in an aluminium heat treating furnace(1991) Hart, Roderick William Wenham; Smuts, D. J.This dissertation is primarily concerned with investigating and improving the degree of accuracy and precision that may be achieved from temperat~re measurements made utilising nickel-chromium/nickel-aluminium (Type K) thermocouples. The practice of heat treating extruded aluminium section creates specific metallurgical properties within section. Development of specialised aluminium alloys has necessitated the use of treatment temperatures,- close to the limit beyond which the alloy experiences undesirable, permanent, metallurgical change. This situation has demanded urgent attention to, in quality assurance terms, the, 'fitness for purpose', of primary temperature sensors. The most established of these sensors, the Type thermocouple, has known problems relating to calibration stability and drift. The substantial amount of furnace control instrumentation and cabling dedicated to measurement from Type K sensors precludes the simple conversion to an alternate sensor type. The more practical option of applying calibration correction factors to existing measuring systems is only feasible if sensor stability characteristics permit measurement traceability to' be established within required uncertainty limits.Item Neural networks approach to process control : the case of processes with long dead times(1999) McLeod, Charles Meredith; Bajic, Vladimir B.This study relates to applications of static artificial neural networks (ANNs) to two basic problems of process control: (a) process model identification, and (b) optimal controller tuning. The emphasis is on model identification, where several novel techniques are introduced. A review of the use of ANNs for determining optimal controller settings is included as a logical adjunct which would make the complete system suitable for realisation as a portable or networked system. Three methods for obtaining good approximations for the parameters of first-order processes with long dead time using artificial neural networks (ANNs) are proposed and described. These are termed in this study: time-domain, frequency-domain and model-based methods. In each case the aim was to develop a brief one-shot test that could be applied with minimal disturbance to a closed loop control system. These methods build on existing techniques, but introduce the following novel aspects: 2. The frequency-domain method makes use of the first 81 components of the FFT without further selection as input to a static ANN to yield process parameter estimates. 3. The model-based method uses a simple single-neuron implementation of an ARX model and uses a static ANN to relate process parameter values to the weights of this neuron. In making the analysis, the process input and output are applied repetitively to the neuron model with delays getting progressively larger. Useful effects arising from this are explored. A technique in which ANN training sets are slightly distorted in a random way during training of a radial basis function is developed as part of the time- and frequencydomain methods. The benefits arising from this technique are demonstrated. These experimental ANN-based control methods are evaluated by means of simulations in which accuracy in the presence of measurement noise and performance with higher order processes is measured and analysed. Although the main theme of this study is first-order-plus-dead-time (FOPDT) processes, the full autotuning scheme is tested with some representative higher order processes. Finally, the composition of a complete autotuning scheme is proposed which includes the automatic generation of controller parameters by means of ANN s.Item A particle swarm optimization approach for tuning of SISO PID control loops(2008) Pillay, Nelendran; Govender, PoobalanLinear control systems can be easily tuned using classical tuning techniques such as the Ziegler-Nichols and Cohen-Coon tuning formulae. Empirical studies have found that these conventional tuning methods result in an unsatisfactory control performance when they are used for processes experiencing the negative destabilizing effects of strong nonlinearities. It is for this reason that control practitioners often prefer to tune most nonlinear systems using trial and error tuning, or intuitive tuning. A need therefore exists for the development of a suitable tuning technique that is applicable for a wide range of control loops that do not respond satisfactorily to conventional tuning. Emerging technologies such as Swarm Intelligence (SI) have been utilized to solve many non-linear engineering problems. Particle Swarm Optimization (PSO), developed by Eberhart and Kennedy (1995), is a sub-field of SI and was inspired by swarming patterns occurring in nature such as flocking birds. It was observed that each individual exchanges previous experience, hence knowledge of the “best position” attained by an individual becomes globally known. In the study, the problem of identifying the PID controller parameters is considered as an optimization problem. An attempt has been made to determine the PID parameters employing the PSO technique. A wide range of typical process models commonly encountered in industry is used to assess the efficacy of the PSO methodology. Comparisons are made between the PSO technique and other conventional methods using simulations and real-time control.