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木本文为随机多变量线性系统建立了全局收敛的M1MO自校正控制器算法。使用这种随机适应控制算法,不论系统和算法的初始条件如何,总能保证系统参数未知条件下的适应控制渐近地达到系统参数已知条件下的最优控制效果。文献[1]、[2]的绝大部分结果和[3]中的随机结果大体上可视为本文结果的特殊情况。使用这种算法,不用在线解方程组,避免了麻烦的矩阵求逆运算。
This paper establishes a globally convergent M1MO self-tuning controller algorithm for stochastic multivariable linear systems. Using this stochastic adaptive control algorithm, the optimal control under unknown conditions of system parameters can be asymptotically guaranteed regardless of the initial conditions of the system and algorithm. The vast majority of the results in [1], [2] and the random results in [3] can generally be considered as special cases of the results in this paper. Using this algorithm, you do not have to solve the equations online, avoiding the cumbersome matrix inversion.