Observer-Based Fuzzy Output-Feedback Control for Discrete-Time Strict-Feedback Nonlinear Systems With Stochastic...

Area of Science:

• Control Engineering
• Nonlinear Systems Theory
• Systems and Control

Background:

• Discrete-time strict-feedback nonlinear systems (DTSFNSs) present challenges due to immeasurable states and noise.
• Observer-based output-feedback control (OBOFC) is crucial for practical applications but complicated by multiplicative process and additive measurement noises.

Purpose of the Study:

• To develop a robust OBOFC strategy for DTSFNSs with both multiplicative and additive noises.
• To address nonlinear modeling uncertainties inherent in real-world systems.
• To ensure exponential mean-square boundedness of the closed-loop system.

Main Methods:

• Design of a state observer to estimate unmeasurable states.
• Development of a novel observer-based backstepping control framework using a variable substitution method to mitigate noise accumulation.
• Integration of fuzzy-logic systems for a fuzzy observer and controller to handle nonlinear uncertainties.
• Derivation of stability criteria using novel weight updated laws.

Main Results:

• A control scheme that effectively estimates system states and compensates for multiplicative and additive noises.
• Demonstrated exponential mean-square boundedness of the closed-loop system under derived stability conditions.
• Successful handling of nonlinear modeling uncertainties through fuzzy logic approximation.

Conclusions:

• The proposed observer-based output-feedback control scheme is effective for discrete-time strict-feedback nonlinear systems with complex noise characteristics and uncertainties.
• Fuzzy logic integration provides a powerful tool for robust control design in the presence of nonlinearities.
• Simulation studies validate the efficacy and robustness of the developed control strategy.