State estimation for coupled PDE systems using Modulation Functions

• Autor: Pumaricra Rojas, David Raul
• Formato: tesis de maestría
• Fecha de Publicación: 2022
• Institución: Pontificia Universidad Católica del Perú
• Repositorio: PUCP-Tesis
• Lenguaje: inglés
• OAI Identifier: oai:tesis.pucp.edu.pe:20.500.12404/22217
• Enlace del recurso: http://hdl.handle.net/20.500.12404/22217
• Nivel de acceso: acceso abierto
• Materia: Sistemas de control adaptable; Biorreactores; Simulación; https://purl.org/pe-repo/ocde/ford#2.02.03

This master thesis is devoted to the state estimation of a particular form of PDE systems, coupled parabolic PDEs with spatial dependent coefficients. This form of PDEs represent some dynamic systems such as Tubular Reactors, Diffusion in lithium-ion cells and Diffusive Gradient in Thin Films sensor. Other methods for this problem use "Backstepping" observers, in which the estimation error system is transformed into another system that is stable, reducing the problem to calculate the Kernel functions making the transformation possible. In some cases this calculation is not simple, also the simulation in real time of the observer system, that is also a PDE, can be difficult. The method presented in this thesis uses the properties of the so-called Modulating Functions in order to estimate the states. The procedure con- sists of generating an orthonormal basis of functions that can represent the state as a combination of them. Then auxiliary systems are formed from the original systems with boundary conditions that help in the simplification of the problem. Resolving these auxiliary systems, result in the calculation of the Modulating kernels. All of these steps can be made offline and do not have to be repeated. The functions are used together with the orthonormal basis in the online part, that consists of an inte- gration of a combination of the kernel functions, inputs and outputs of the system in a time window. Finally, with a matrix multiplication the coefficients for the ba- sis expansion of the state can be obtained, resulting in the desired state estimation. The present method is tested in systems that resemble the forms of the dynamics of Tubular Reactors and the performance is compared to other methods.