Neuroadaptive Control for Nonlinear Systems With Piecewise and Discontinuous Output Constraints
针对工程中常见但研究不足的分段不连续输出约束问题，提出一种集成两个新移位函数和障碍李雅普诺夫函数的神经自适应控制框架，无需调整控制器结构即可处理多种约束场景。
The piecewise and discontinuous output constraints are prevalent in practical engineering systems but remain insufficiently explored in the literature. Unlike existing results, the discontinuous constraints considered here exhibit two salient characteristics: 1) the bounded constraint boundary function undergoes a jump discontinuity at a specific instant during the initial operational period and 2) the system output becomes unconstrained thereafter. These features render traditional methods inadequate because the derivatives of the constraint boundary function do not exist. To address this problem, we propose a systematic neuroadaptive control framework for nonlinear systems that integrates two novel shift functions with a new barrier Lyapunov function (BLF). The presented control scheme not only ensures good tracking performance under such piecewise and discontinuous output constraints but also can be applied to several other common yet critical constraint scenarios without involving any adjustment to the controller structure. Theoretical analysis and simulation results verify the effectiveness and practicality of the proposed approach.