Model state feedback control algorithm for uncertain nonlinear systems with input multiplicities

A nonlinear system is said to have input multiplicities when at the steady state more than one set of input values produces the same output value. Numerous real chemical processes, such as binary distillation columns, continuous stirred tank reactors (CSTR) with recycle, and fluid catalytic cracking (FCC) units, exhibit such characteristics. Research has shown that input multiplicities can severely restrict the range of operation of linear control systems and play a strong role in the selection of control structures.; In this thesis, we present a control algorithm for stable, uncertain nonlinear SISO systems with input multiplicities. The algorithm is shown to have yielded a desirable result for both reachable and unreachable setpoints.; We analyzed the steady state stability of the algorithm and the impact of the model selection on the steady state stability and performance. We proposed a model selection procedure for obtaining an optimal model for the steady state performance and stability. We presented tuning procedures for the control algorithm. For unreachable setpoints, we presented an outer loop setpoint adjustment algorithm so that the process output will reach a point closest to the setpoint requested.; Finally, we discussed several possible extensions to the algorithm and the issues related to the extensions.