Different types of (bio)chemical processes are modeled by partial differential equations, generally known as distributed parameter systems. Axial dispersion reactors, separation columns, and the flow inside a pipeline are a few examples. In this contribution, a tubular biochemical reactor nonlinear model is initially considered. This dynamical model can describe a large class of bioprocesses, such as in wastewater treatment [1] or water treatment [2].
First, the possible existence of different equilibrium profiles is shown in the dynamic analysis of the non-linear model [3]. Then, the control and state estimation problems are considered for a linearized version of the system around a desired equilibrium profile. It is considered that the system is under output delay due to the necessary analysis that needs to be carried out in the output of a biochemical process. In the same line, the output is also considered to present measurement uncertainties. Furthermore, the system is considered multi-rate for the actuation and sampling times.
When it comes to the stabilization of distributed systems, the complexity associated with the infinite-dimensional nature of the system has been addressed with the application of different methodologies, for example, backstepping [4], the linear quadratic regulator [5], and inertial manifolds [6].
Here, we consider an extension of the model predictive control for linear systems developed in previous contributions [7, 8]. As the controller requires state feedback, a Kalman filter is developed for state reconstruction based on the delayed output [9]. Finally, the difference in the actuation and sampling time also needs to be considered in the controller design.
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