This paper develops a designated-time adaptive tracking control strategy for nonlinear systems subject to multiple sources of uncertainty, including output constraints, unmodeled dynamics, and unknown disturbances. By incorporating an enhanced fuzzy logic system for parameter estimation and a bounded command filtering approach, this work proposes a systematic tracking control scheme that effectively avoids the issue of computational complexity explosion. To address the significant uncertainties induced by constraints, an asymmetric barrier Lyapunov function is used for analysis and design under the condition of known control coefficients. Furthermore, a controller constructed based on an event-triggered mechanism ensures uniform boundedness and designated-time convergence of all signals. The feasibility and effectiveness of the proposed control method are validated through a practical application case.

This manuscript considers the state feedback stabilization problem for a class of stochastic high-order and low-order nonlinear systems with time-delay. Compared with the previous results, a distinctive feature to be studied is that the considered systems involve high-order, low-order, intricate stochastic diffusion terms and time-delay simultaneously. First, the homogeneous domination approach and suitable coordinate transformations are introduced to obtain the updating laws. Then, a state feedback controller is devised to make the closed-loop systems globally asymptotically stable in probability. Finally, a simulation example is shown to prove the proposed approach powerfully.