Adaptive Tracking Control for Uncertain Nonlinear Systems with Full-State Quantization

This thesis investigates adaptive trajectory-tracking control for uncertain nonlinear systems with full-state quantization. The considered setting is motivated by networked control systems with limited communication bandwidth, where only quantized state measurements are available. This introduces signal discontinuities, quantization errors, and additional difficulties in controller design and stability analysis. First, a command-filtered adaptive controller is proposed for flexible-joint robots with full-state quantization. The command filter avoids the direct differentiation of discontinuous quantized virtual control signals, while the adaptive law compensates for uncertain nonlinear dynamics and quantization effects. Second, a prescribed-performance control method is developed for flexible-joint robots under fullstate quantization. The proposed method guarantees desired transient and steady-state tracking behavior and is validated on a Quanser flexible-joint robot platform. Third, an adaptive fixed-time tracking controller is designed for uncertain nonlinear systems with full-state quantization. Fuzzy logic systems are used to compensate for unknown dynamics, and the tracking errors converge to a neighborhood of the origin within a fixed time independent of the initial conditions. Finally, an adaptive fault-tolerant control method is proposed for underactuated surface vessels with state quantization, actuator faults, uncertainties, and external disturbances. Theoretical analysis and simulation or experimental results demonstrate that the proposed methods ensure bounded closedloop signals and satisfactory tracking performance under communication constraints. Overall, this thesis provides a systematic adaptive control framework for nonlinear systems operating under full-state quantization. By addressing communication constraints together with uncertainty, performance requirements, fixed-time convergence, and actuator faults, the proposed methods improve the applicability of adaptive control in bandwidth-limited networked environments.