Abstract
Some of the most difficult problems associated with process control are due to process nonlinearity, manipulated variable constraints, uncertain parameters and unmeasured variables. In this paper a nonlinear programming approach is developed to estimate process parameters, unmeasured state variables and process disturbances. A constrained optimization-based procedure is also used to maintain a desired output variable trajectory, similar to techniques that have proven successful for linear systems. The process model, characterized by a set of nonlinear differential equations, is transformed into algebraic equations using orthogonal collocation on finite elements. A system with inverse response characteristics and a bioreactor model are used as examples.
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Bequette, B.W. (1990). Process control using nonlinear programming techniques. In: Bensoussan, A., Lions, J.L. (eds) Analysis and Optimization of Systes. Lecture Notes in Control and Information Sciences, vol 144. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0120028
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DOI: https://doi.org/10.1007/BFb0120028
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