Through learning and remembering the adjusting rule of PID parameters, the PID parameters are adjusted on line by the network.
该网络通过学习并记忆PID参数调整规则，实现了在线调整PID参数。
Combine blur control with general PID control, on line self-adjusting PID parameters according to different error and error variety-rate, which is called PID parameters self-tuning blur controller.
将模糊控制与常规pid控制相结合，根据不同的误差、误差变化率对PID的参数进行在线自动调整，这就是PID参数自整定模糊控制器。
Through combining Fuzzy logic with PID controller and adjusting control parameters in on-line ways, it can perfect the properties of PID controller and improve the precisions of control system.
接着将模糊控制器和PID控制器通过自适应因子结合起来，在线自调整控制参数，进一步完善了PID控制器的性能，提高了系统的控制精度。
The network is used to remember adjusting rules of PID parameters by learning so the network can adjust PID parameters on line by rules.
该网络通过学习记忆PID参数调整的基本规则，实现了PID控制器参数的在线调整。
An active noise self-tuning model predictive control approach is derived. An on-line learning algorithm is proposed for adjusting the uncertain model parameters.
将预测控制方法应用到有源噪声控制领域，给出了一种参数在线自适应算法，该算法的收敛速度不受次级声路径响应的影响。
An active noise self-tuning model predictive control approach is derived. An on-line learning algorithm is proposed for adjusting the uncertain model parameters.
将预测控制方法应用到有源噪声控制领域，给出了一种参数在线自适应算法，该算法的收敛速度不受次级声路径响应的影响。
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