For high performance model based control applications the state and parameter estimation algorithms are essential. Furthermore the accuracy of the resulting estimates highly depends on what is being measured. In this work we address the output channel selection problem by making use of the degree of observability measures defined by the observability gramians of the associated system and possible different sensor configurations. The observability gramians for large scale and nonlinear first principle models are difficult to compute. Instead the data based approximations, the empirical observability gramians, are constructed. The degree of observability measures are used for comparing the spectral properties of the observability gramians to decide the sensor configuration. The output channel selection procedure is applied to an industrial membrane filtration system.
|Number of pages||6|
|Publication status||Published - Jun 2016|
|Event||11th IFAC International Symposium on Dynamics and Control of Process Systems, Including Biosystems (DYCOPS-CAB 2016) - Trondheim, Norway|
Duration: 6 Jun 2016 → 8 Jun 2016
Conference number: 11