Tytuł pozycji:
Object-oriented DSP implementation of neural state estimator for electrical drive with elastic coupling
The study presents results and procedure of object-oriented and test-driven
implementation of neural-network-based state estimator. The presented algorithm has
been developed for estimation of the state variables of the mechanical part of electric
drive with elastic coupling. Estimated state variables – load speed and shaft stiffness
torque – can be used in speed control process for reducing mechanical vibrations of
working machine. The basic objective was to create a simple, extensible and readable
program code, performing the task of state estimation of the considered system. The
target platform is a DSP (Digital Signal Processor) from SHARC (Super Harvard
architecture Single-Chip Computer) family, which allows for hardware acceleration of
matrix operations. The IDE (Integrated Development Environment) available for the
selected platform made it possible to write program in C++. The usage of UML
(Unified Modelling Language) in the development of control software was discussed.