以生物发酵模型为背景，考察了一般非线性系统的模型修正与状态估计问题。利用随机干扰下状态过程的高斯分布性质，由实测样本点构造似然函数，然后应用优化程序进行修正与估计 Taking the biofermentation model as a background, the problem of model revision and state estimation for general nonlinear systems is investigated. Using the Gaussian distribution property of the state process under the random disturbance, a likelihood function is constructed from the measured sample points, and then the optimization procedure is used to correct and estimate