CAJ | 학술논문

对具有滞后工业过程稳态优化进程提出加权超前局部对称双积分型迭代学习控制算法.基于理想轨线与控制系统的实际输出动态信息,提出基本的迭代学习控制算法并分析和论证算法的收敛性,给出局部对称积分区间参数的确定策略.数字仿真表明,加权超前局部对称双积分型迭代学习控制算法能有效消除噪声对系统输出信号的影响并能改善滞后工业过程稳态优化进程中控制系统的动态品质,如减少超调,缩短过渡时间,加快响应速度等.
대구유체후공업과정은태우화진정제출가권초전국부대칭쌍적분형질대학습공제산법.기우이상궤선여공제계통적실제수출동태신식,제출기본적질대학습공제산법병분석화론증산법적수렴성,급출국부대칭적분구간삼수적학정책략.수자방진표명,가권초전국부대칭쌍적분형질대학습공제산법능유효소제조성대계통수출신호적영향병능개선체후공업과정은태우화진정중공제계통적동태품질,여감소초조,축단과도시간,가쾌향응속도등.
The weighted leading local-symmetrical-double-integral-type iterative learning control algorithm is studied for dynamics of industrial processes with time delay in steady-state optimizing. Based on the desired trajectory and real output dynamical information of the control system, a basic iterative learning control algorithm is suggested, its ε-convergence is derived, and the interval length of local symmetrical double integral is determined. Digital simulations show that the iterative learning control algorithm can effectively eliminate the influence of the noise on output signal and can remarkably improve the dynamical performance of the control systems in steady-state optimizing, such as to decrease the overshoot, shorten the settling time, accelerate the response, etc.