The parameters of the neural network PID controller are modified on line by the improved conjugate gradient.

并用这种改进的共轭梯度法对神经网络PID控制器参数实现在线修正。

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Trajectory sensitivity approach is used to assess the gradient of the PSS and SVC parameters on the objective function and then conjugate gradient approach is applied to find the optimum solution.

通过计算发电机转速和无功补偿节点电压变化量对各控制器参数的轨迹灵敏度，获得目标函数对各控制器参数的梯度，以便于用共轭梯度法寻找最优解。

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Results Under the condition of the conjugate prior distribution, the prior parameters computed by three methods were similar.

结果在共轭先验分布的条件下，先验矩、分位数、众数与分位数三种方法确定的先验分布参数结果一致。

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