Reduced order state estimation for a class of impulsive switched systems with unknown inputs

Area of Science:

• Control Systems Engineering
• Nonlinear Dynamics
• Estimation Theory

Background:

• Impulsive switched systems are prevalent in various engineering applications.
• Estimating states and switching signals in these systems is challenging due to unknown inputs and inherent impulsivity.
• Existing methods often struggle with the combined effects of unknown inputs and system impulsivity.

Purpose of the Study:

• To develop a robust method for state and switching signal estimation in impulsive switched systems with unknown inputs.
• To effectively mitigate the impulsive effects introduced by unknown inputs.
• To ensure exponential decay of estimation errors.

Main Methods:

• A two-step approach involving dedicated estimators for switching signal and subsystem identification.
• Utilizing a reduced-order estimator for inaccessible states.
• Employing an output derivative-based method to handle unknown inputs.
• Leveraging common Lyapunov function and Linear Matrix Inequality (LMI) techniques.

Main Results:

• The proposed method successfully estimates states and switching signals in the presence of unknown inputs.
• Impulsive effects caused by unknown inputs are effectively eliminated by incorporating the estimated switching signal.
• Exponential decrease in estimation errors is achieved under specific conditions.
• Simulation results demonstrate superior efficiency and effectiveness compared to single-estimator approaches.

Conclusions:

• The developed method offers a robust solution for state and switching signal estimation in complex impulsive switched systems.
• The technique effectively addresses the challenges posed by unknown inputs and system impulsivity.
• The findings provide a valuable contribution to the field of control systems and estimation theory.