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Theses and dissertations (Engineering and Built Environment)

Permanent URI for this collectionhttp://ir-dev.dut.ac.za/handle/10321/10

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    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.
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    A particle swarm optimization approach for tuning of SISO PID control loops
    (2008) Pillay, Nelendran; Govender, Poobalan
    Linear 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.