CAJ | 학술논문

针对实际工业常见的定点跟踪控制问题，通过数学变换，将原系统最优跟踪控制问题转化为新系统最优调节问题，以跟踪误差作为新系统的状态量，引入ε-自适应动态规划算法(ε-ADP)求解HJB方程，并以两个BP神经网络分别用于近似性能指标函数和最优控制，从而得到ε-最优跟踪控制。仿真实验表明，所设计的控制器可以在有限时间内将状态跟踪到目标值，并使得性能指标函数近似最优。
침대실제공업상견적정점근종공제문제，통과수학변환，장원계통최우근종공제문제전화위신계통최우조절문제，이근종오차작위신계통적상태량，인입ε-자괄응동태규화산법(ε-ADP)구해HJB방정，병이량개BP신경망락분별용우근사성능지표함수화최우공제，종이득도ε-최우근종공제。방진실험표명，소설계적공제기가이재유한시간내장상태근종도목표치，병사득성능지표함수근사최우。
In order to deal with the common fix-point tracking control problems in actual industrial systems, a mathematical transformation is developed to change the original system optimal tracking control problem to an optimal regulator problem of a new system. The state variables of the new sys-tem are the tracking error. ε-adaptive dynamic programming (ε-ADP) is used to solve HJB equation while two BP neural networks are used to approximate the performance index function and optimal control. Thus ε-optimal tracking control is obtained. Simulation results show that the controller de-signed can track a state to the target and make the performance index function converges to optimal.