As a means of converting abundant waste to wealth, thermal conversion of waste plastics of four different types (low and high density polyethylene (LDPE and HDPE), polypropylene (PP) and mixed plastics) was carried out in a batch reactor made of stainless steel at temperatures between 170 and 3000 0 C under atmospheric pressure. The vapor produced from melting the plastics was condensed to form the liquid hydrocarbon (fuel oil) product. Standards were followed for each of the waste plastics during the production process of the liquid fuel oil. The effect of reaction time and product yield were investigated. The physical properties measured include product density and specific gravity. The liquid products formed were characterized using FT-IR spectrometer (Spectrum 100 Perkin-Elmer). The heat combustion properties of the fuels produced were compared using ASTM D240. Also the API gravity and Sulphur content analysis were carried out using the ASTM D4052 and 4053 respectively. The chemical properties of the liquid product were compared for each of the samples and it was found that they vary from each waste plastic. Each of the liquid products contained low sulfur, but each of them varied from each other.

The immiscibility of vegetable oil in methanol provides a mass transfer challenge in the early stages of Transesterification reaction in the production of biodiesel. It is of a great significance to design high-performance nonlinear controllers for efficient control of these nonlinear processes to achieve closed-loop system's stability and high performance of a biodiesel CSTR. A mathematical model capable of predicting the performance and behaviour of a CSTR has been developed and evaluated. In this work, a comprehensive design procedures based on model predictive control (MPC) have been proposed to efficiently deal with the design of gain-scheduled controllers, controller tuning, optimal controllers and time-varying for nonlinear systems. Since all the design procedures proposed in this work rely strongly on the process model, the first difficulty addressed in this paper is the identification of a relatively simple model of the nonlinear processes under study. The second major difficulty is the analysis of stability and performance for such models using nonlinear control theory of a robust control approach. In the current work, the nonlinear model is approximated by a nominal linear model combined with a mathematical description of model error (due to nonlinearity) to be referred to (in this work) as model uncertainty. The robust control theoretical tools developed are used for the design of gain-scheduled Proportional-Integral-Differential (PID) control and gain-scheduled Model Predictive Control (MPC) in which the MPC method achieves the steady-state optimal set-points of the biodiesel Transesterification reactor.

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