Adaptive control with nonlinear filtering
Nonlinear filters are not commonly used in parameter adaptive control. They make, however, a noteworthy alternative especially when state space models and control algorithms are used. In practice most of the well- known nonlinear filters like the extended Kalman filter suffer computational complexity and robustness problems. In the paper a filter is introduced which is not new but less well known and suffers less with these problems. Relationship with extended Kalman-type filters is shown. It is further shown how simultaneous state and parameter estimation can be done without using extended state techniques. Adaptive control design is based on a linear state space model and per interval quadratic performance index. A multivariable PI-type controller is obtained, the parameters of which can be easily calculated. As a case example application to servo control of a real life hydraulic manipulator is considered.
simultaneous state and parameter estimation
scientific article; zbMATH DE number 3904440