Adaptive output feedback control for uncertain nonlinear systems with quantized input and output.

Area of Science:

• Control Theory
• Nonlinear Systems
• Systems Engineering

Background:

• Nonlinear systems present challenges in control due to uncertainties.
• Quantization in system inputs and outputs complicates control design.
• Existing methods may struggle with both input and output quantization simultaneously.

Purpose of the Study:

• Develop an adaptive stabilization control scheme for uncertain nonlinear systems.
• Address the challenges posed by quantized input and output signals.
• Ensure system stability and minimize residual errors under quantization effects.

Main Methods:

• Introduced a finite-time filter for discontinuous quantized output, ensuring continuity and sector-bound properties.
• Designed an observer to estimate unmeasurable states.
• Utilized dynamic surface control to avoid repeated derivatives of the filtered quantized output.

Main Results:

• The proposed finite-time filter yields a continuous and sector-bounded filtered quantized output.
• The observer successfully estimates unmeasurable states.
• The adaptive control scheme guarantees stabilization error convergence to a small residual set.

Conclusions:

• The developed adaptive stabilization control scheme effectively handles uncertain nonlinear systems with quantized input and output.
• The combination of finite-time filtering, observer design, and dynamic surface control provides a robust solution.
• The approach demonstrates practical applicability even with coarse quantizers, adjustable via design parameters.