NTAC-02 ABB 具有较强的鲁棒性和不敏感性

NTAC-02 ABB 具有较强的鲁棒性和不敏感性

NTAC-02以现代控制理论为基础，融入模糊控制、专家控制、神经网络控制，以形成高智能化的自动控制系统为现代自动化控制领域的发展方向。模糊控制依靠模糊控制器在执行控制过程中通过不断获取现场信息，及时调整模糊控制规律，改善系统性能，具有自学习功能。

由于具有较强的鲁棒性和不敏感性，模糊控制使得控制系统的稳定性获得改善，可以提高控制精度、抑制振荡等现象；专家控制是人工智能领域的一个重要研究方法，在提高控制系统的灵活性和智能化方面具有优越性；

神经网络控制从仿生学角度出发，对人体大脑神经系统进行模拟，使机器具有感知、学习和推理能力，神经网络能够不断逼近任意复杂的非线性关系，能学习与适应严重不确定的系统的动态性能，所有信息都等势分布储存于网络内各神经元，因此有极强的鲁棒性和容错性，在解决高度非线性和严重不确定系统控制方面有巨大潜力。 

NTAC-02 ABB 具有较强的鲁棒性和不敏感性

Based on modern control theory, NTAC-02 integrates fuzzy control, expert control and neural network control to form a highly intelligent automatic control system as the development direction of modern automation control field. The fuzzy control relies on the fuzzy controller to adjust the fuzzy control law in time to improve the system performance by obtaining the field information continuously during the control process, and has the self-learning function.

Because of its strong robustness and insensitivity, fuzzy control can improve the stability of the control system, improve the control precision and suppress the oscillation. Expert control is an important research method in the field of artificial intelligence, which has advantages in improving the flexibility and intelligence of control system.

From the perspective of bionics, neural network control simulates the human brain nervous system, enabling the machine to have the ability of perception, learning and reasoning. The neural network can constantly approach any complex nonlinear relationship, and can learn and adapt to the dynamic performance of the seriously uncertain system. All information is equipotential distributed and stored in each neuron in the network, so it has strong robustness and fault tolerance. It has great potential in solving highly nonlinear and seriously uncertain system control.