Development and applications of novel optimal control algorithms
The main concern of this thesis is to advance and improve the existing knowledge of a dynamic optimal control technique known as DISOPE. so as to make it attractive on one hand for its implementation in the process industry and, on the other hand, as a novel nonlinear optimal control algorithm. The main feature of the technique is that it has been designed so as to achieve the correct optimum of the process in spite of inaccuracies in the mathematical model employed in the computations. Several extensions of the basic continuous time DIS OPE technique are proposed in this work. For the development of the algorithms, emphasis is placed on making the techniques implementable in digital computer based industrial process control problems. These extensions include discrete-time. and set-point tracking versions, extensions for handling control and state dependent inequality constraints. and a hierarchical version. Applications of DISOPE are proposed in the following areas: nonlinear predictive control, predictive optimising control based on adaptive state-space linear dynamic models, and batch process optimisation. All the algorithms and techniques proposed in this thesis have been implemented in software and tested with relevant simulations. These studies include dynamic simulations of low order chemical reaction systems and studies on the dynamic optimisation of an industrial-scale multicomponent distillation column using a rigorous process simulator. Comparisons with existing techniques are provided and suggestions are made for future research in the area treated in this thesis.