USDE-Based Sliding Mode Control for Servo Mechanisms With Unknown System Dynamics

Algorithms for U-Model-Based Dynamic Inversion (UM-Dynamic Inversion) for Continuous Time Control Systems

“…(4) U-model-based design procedure is more general and effective for designing a linearly behaved control system, which provides new insight and solutions to design the controller. (5) U-control can be applied together with the other well-developed control system design methods, such as pole placement control, sliding mode control, general predictive control, adaptive, and Smith predictive control [20,21]. (6) It should be noted that unless the plant model is accurately known, U-model dynamic inversion is very sensitive to internal uncertainties, so the whole control system performance.…”

Hesitant Bipolar-Valued Fuzzy Soft Sets and Their Application in Decision Making

“…With the continuous development of fuzzy set, soft set, and uncertainty theory, artificial intelligence has received extensive attention around the world. Related control schemes have also achieved fruitful results [26][27][28][29][30][31][32][33][34][35][36][37][38]. More detailed research on the uncertainty measures of fuzzy soft sets and other models can provide a reliable mathematical foundation for the development of cybernetics.…”

Terminal Traction Control of Teleoperation Manipulator With Random Jitter Disturbance Based on Active Disturbance Rejection Sliding Mode Control

“…However, ISMC exhibits insensitivity to the matched and unmatched uncertainties throughout the system response. In [23], an unknown system dynamics estimator (USDE) based sliding mode control was proposed for servo mechanisms with unknown dynamics and modeling uncertainties. To reduce chattering, a novel reaching law is formulated based on hyperbolic functions to ensure that the sliding mode variable infinitely approaches the equilibrium point, instead of crossing it.…”