Integral filters from a new viewpoint and their application in nonlinear control design

This paper looks at linear integral filters from a new viewpoint in time domain and use them for real-time nonlinear control design. In nonlinear control application, the signal may be from measurement and/or from composite states. It may be polluted by measurement noise or disturbance which are not necessarily white and thus cannot be addressed in a transfer function approach. Thus it may not be theoretically and/or practically differentiable or its numerical derivative leads to a bad result. The new viewpoint for integral filters are based on the solution of an inverse Taylor series problem. Several models are proposed and their existence and stability are primarily considered. Simulation results are used to show dynamic properties of these filters. An example for the application of these filters in multi-surface dynamic backstepping sliding mode control design of a nonlinear system with unmatched uncertainties is given