In the chemical industry, the control of pH is a well-known problem that presents\ud difficulties due to the large variations in its process dynamics and the static nonlinearity\ud between pH and concentration. pH control requires the application of advanced control\ud techniques such as linear or nonlinear adaptive control methods. Unfortunately, adaptive\ud controllers rely on a mathematical model of the process being controlled, the parameters\ud being determined or modified in real time. Because of its characteristics, the pH control\ud process is extremely difficult to model accurately.\ud Fuzzy logic, which is derived from Zadeh's theory of fuzzy sets and algorithms,\ud provides an effective means of capturing the approximate, inexact nature of the physical\ud world. It can be used to convert a linguistic control strategy based on expert knowledge,\ud into an automatic control strategy to control a system in the absence of an exact\ud mathematical model. The work described in this thesis sets out to investigate the\ud suitability of fuzzy techniques for the control of pH within a continuous flow titration\ud process.\ud Initially, a simple fuzzy development system was designed and used to produce an\ud experimental fuzzy control program. A detailed study was then performed on the\ud relationship between fuzzy decision table scaling factors and the control constants of a\ud digital PI controller. Equation derived from this study were then confirmed\ud experimentally using an analogue simulation of a first order plant. As a result of this\ud work a novel method of tuning a fuzzy controller by adjusting its scaling factors, was\ud derived. This technique was then used for the remainder of the work described in this\ud thesis.\ud The findings of the simulation studies were confirmed by an extensive series of\ud experiments using a pH process pilot plant. The performance of the tunable fuzzy\ud controller was compared with that of a conventional PI controller in response to step\ud change in the set-point, at a number of pH levels. The results showed not only that the\ud fuzzy controller could be easily adjusted to provided a wide range of operating characteristics, but also that the fuzzy controller was much better at controlling\ud the highly non-linear pH process, than a conventional digital PI controller. The fuzzy\ud controller achieved a shorter settling time, produced less over-shoot, and was less\ud affected by contamination than the digital PI controller.\ud One of the most important characteristics of the tunable fuzzy controller is its ability\ud to implement a wide variety of control mechanisms simply by modifying one or two\ud control variables. Thus the controller can be made to behave in a manner similar to that\ud of a conventional PI controller, or with different parameter values, can imitate other\ud forms of controller. One such mode of operation uses sliding mode control, with the\ud fuzzy decision table main diagonal being used as the variable structure system (VSS)\ud switching line. A theoretical explanation of this behavior, and its boundary conditions,\ud are given within the text.\ud While the work described within this thesis has concentrated on the use of fuzzy\ud techniques in the control of continuous flow pH plants, the flexibility of the fuzzy\ud control strategy described here, make it of interest in other areas. It is likely to be\ud particularly useful in situations where high degrees of non-linearity make more\ud conventional control methods ineffective
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