CAJ | 학술논문

针对一类具有未知时变时滞的不确定高阶非线性系统，基于增加幂次积分方法，提出了一种非光滑状态反馈自适应神经网络动态面控制设计方案。通过构造适当的 Lyapunov-Krasovskii 泛函处理了未知时变时滞不确定项；通过利用神经网络权值范数的适当形式幂次函数，将神经网络用于对在单步递推中所构造的未知函数进行建模；采用动态面技术，解决了“微分爆炸”问题。所提控制方案能够保证闭环控制系统的状态量和跟踪误差半全局一致终结有界。最后，仿真算例结果表明了该方案的有效性。
침대일류구유미지시변시체적불학정고계비선성계통，기우증가멱차적분방법，제출료일충비광활상태반궤자괄응신경망락동태면공제설계방안。통과구조괄당적 Lyapunov-Krasovskii 범함처리료미지시변시체불학정항；통과이용신경망락권치범수적괄당형식멱차함수，장신경망락용우대재단보체추중소구조적미지함수진행건모；채용동태면기술，해결료“미분폭작”문제。소제공제방안능구보증폐배공제계통적상태량화근종오차반전국일치종결유계。최후，방진산례결과표명료해방안적유효성。
Based on the adding a power integrator method,a non-smooth state-feedback adaptive neural net-work dynamic surface control scheme is proposed for a class of uncertain high-order nonlinear systems with un-known time-varying delays.The appropriate Lyapunov-Krasovskii functionals are chosen to deal with the un-known time-varying delay uncertainties.The proper power function of the norm of the neural network’s power value is adopted to model the constructed unknown function in every step.And the problem of “explosion of complexity”can be solved by adopting the dynamic surface control.The designed controller can guarantee that all the states of the closed-loop control systems and the tracking error are semi-global uniformly ultimately bounded.The results of a simulation example demonstrate the effectiveness of this scheme.