摘要
针对苛化温度的高阶非线性、时变性、多干扰及大时滞等特点,提出来一种基于免疫机理的单神经PI D控制算法。该算法利用T细胞免疫机理调节单神经元的比例系数K,克服单神经元PID控制响应速度慢的缺点。在Simulink中进行苛化温度的动态仿真研究,并通过加入高斯白噪声及变换对象模型,验证该算法的鲁棒性及自适应能力。仿真结果表明:该算法既继承了单神经元PID算法较强的抗干扰能力与自适应能力,又具有较快的动态响应速度。该算法的实际应用也验证其具有可行性。
Causticizing process was characterized by high order nonlinear, time-varying, multi disturbance and large time-delay. Aimed at these problems, in this paper was proposed a single neuron PID algorithm based on immune mechanism. Using the proportionality coefficient K of single neuron by T cell immune tuning mechanism, the algorithm regulates can overcome shortcomings of slowly response performance of single neuron PID algorithm. The causticizing temperature＇s dynamic simulation was studied by adding white Gaussian noise and changing mathematical model to prove the robustness and adaptive ability of the algorithm. The simulation result shows that the algorithm succeeds the advantages of single neuron PID method which has the ability of strong anti-interference and self- adaption. At the same time, the algorithm also has faster dynamic response rate.
出处
《中华纸业》
CAS
2016年第16期46-51,共6页
China Pulp & Paper Industry
基金
江苏高校优势学科建设工程资助项目(PAPD)
关键词
苛化温度
免疫机理
单神经元
比例系数
temperature in causticizing process
immune mechanism
single neuron
proportionality coefficient
