| 1. | Neutralization process is a typical nonlinear process with pure time delay . this process ca n ' t be controlled effectively with conventional linear control method
中和过程是一个典型的非线性、纯时延过程，用常规的线性控制方法不可能对其进行有效控制。 |
| 2. | Fuzzy control fit the control of nonlinear , time lag system . it especially fits the control of neutralization process . so fuzzy control is employed in the control system as a feed forward control
模糊控制完全是在操作人员控制经验的基础上实现对系统的控制，无需建立数学模型，具有较强的鲁棒性，适用于非线性、时变、时滞系统的控制，对中和过程的控制尤其适合。 |
| 3. | To nonlinear plants with uncertainties , the model - free control method with two neurons is proposed . applied to a ph neutralization process with heavy nonlinear character , the experiments are made to show the effectivenes and robustness of the proposed method 5
针对具有严重非线性和不确定性的受控对象，提出了一种双神经元非模型控制方法，并以ph中和过程为背景进行了仿真控制实验，仿真结果验证了该方法的鲁棒性和有效性； 5 |
| 4. | The neuron control method with self - tuning gain is proposed for a ph neutralization process . in this control system , the fuzzy t - s model is used to predict the control signal . the neuron controller gain is calculated according to the parameter estimation and experience formulas
针对具有严重非线性特性的ph中和过程，提出了一种模糊增益自整定神经元控制方法，这种方法采用t - s模糊推理估计下一时刻的控制量，并通过参数估计和经验公式来计算出神经元控制器的增益。 |
| 5. | In this paper , the t - s model of ph neutralization process was identified via fuzzy c mean clustering and orthogonal least - squares algorithm ; on the basis of it the generalized predictive controller was designed . the effective performance of the controller was validated by matlab simulation
论文首先采用模糊c均值算法和正交最小二乘法辨识ph值中和过程的t - s模糊模型,然后以此模型为基础设计广义预测控制器,实现系统的最优控制,最后通过matlab仿真验证了该模糊预测控制器的有效性。 |
| 6. | By considering the nonlinear characteristic of ph neutralization process , a nonlinear dmc control scheme , based on the cm ac model which is used to model the titration equation , is proposed to overcome the nonlinear disturbance caused by the unknown spices existing in the process stream . the effectiveness of this strategy has been verified via simulation
通过对ph中和过程的分析，针对常规dmc方法在控制该过程中存在的问题，提出一种基于cmac的非线性dmc控制算法，并通过仿真验证了该算法能有效地克服常规浙门刁、学协l学位论义仰i儿d c方沿存在的不足，有效地改故了控十帅l能。 |
