Abstract
In most cases, the entire simulation model of multivariable control systems itself is composed of different multidimensional subsystems. These can be process models, feedback control systems, state observer schemes, as well as deterministic signal models for reference variables and disturbances. The elements of the coupled multivariable subsystems are obtained by theoretical and numerical modelling and controller design procedures, using matrix-oriented state-space techniques, as well known. The presented program system SIMCOS, therefore, bases on the state-space formulation of multivariable systems and subsystems. For several reasons, SIMCOS is more suitable to simulations of complex linear systems than block-oriented and equation-oriented simulation languages, using scalar variables. Within the program SIMCOS (simulation of multivariable control systems) arbitrary subsystem structures can be defined, using a symbolic and matrix-oriented notation, and therefore it is more flexible than other multivariable simulators with predefined system structures. The composition of the entire simulation model is performed automatically, structure and dimension error detection included. In order to obtain high integration rates, a two pass simulation method with data reduction and zero-element detection in matrix calculations have been applied.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
