Design of output feedback controller for stochastic feedforward systems with unknown measurement sensitivity

Area of Science:

• Control Systems Engineering
• Stochastic Systems Analysis
• Nonlinear Dynamics

Background:

• Stochastic feedforward systems present control challenges due to unknown measurement sensitivity.
• Designing output feedback controllers requires addressing uncertainties in system parameters.

Purpose of the Study:

• To develop an output feedback control strategy for stochastic feedforward systems with unknown, bounded measurement sensitivity.
• To ensure asymptotic stability in probability for the closed-loop system.

Main Methods:

• Utilizing low-gain linear K-filters without direct output information.
• Employing a backstepping-based gain design for controller construction.
• Applying stochastic stability theory for system analysis.

Main Results:

• A novel output feedback controller was designed for systems with unknown measurement sensitivity.
• The controller guarantees asymptotic stability in probability for the closed-loop system.
• Effectiveness demonstrated through a nonlinear liquid level control resonant circuit system.

Conclusions:

• The proposed control scheme effectively addresses output feedback control for stochastic systems with unknown measurement sensitivity.
• The backstepping-based approach combined with K-filters provides a robust solution.
• The method is validated by practical application in a liquid level control scenario.