Adaptive neural control for uncertain switched nonlinear systems with a switched filter-contained hysteretic quantizer

Neural-Networks-Based Adaptive Fault-Tolerant Control of Nonlinear Systems With Actuator Faults and Input Quantization

“…Consider the non-strict-feedback system (1) with Assumptions 1-2 taken into account, along with actuator faults (2) and hysteresis quantizer (3). Given bounded initial conditions, the proposed control approach, comprising the actual controller ω (35), virtual control law ζ i (17), (26), and adaptive laws ηi (18), (27), and (39), ensures the boundedness of all signals within the closed-loop system. Furthermore, the tracking error…”

“…To the best of our knowledge, however, the fault-tolerant control which takes into input quantization hasn't received any attention in the current literature. Recent years have seen a rise in the prominence of quantized control in the discipline of control engineering and in hybrid, digital, and networked control systems, it has been widely used [27]. In order to create a strong nonlinear behavior during control design, a quantizer can be considered as a mapping from a continuous region to a discrete set of numbers, primarily as piecewise constant functions of time [28].…”