阻尼累加离散灰色预测的Smith预估智能灌溉系统

灌溉系统具有非线性、多干扰和时滞性等特点，为实现灌溉控制的智能决策与精准灌溉，提出基于阻尼累加离散灰色预测的Smith预估变论域模糊PID灌溉控制模型（DADGM-SVUFP）。针对模糊PID控制器控制精度不高、适应性不强等不足，设计指数函数型伸缩因子自适应调整模糊变量论域，采用Smith预估补偿器消除系统时滞性影响，改善系统适应性和鲁棒性。结合离散灰色预测（DGM）和阻尼累加灰色预测（DAGM）模型的预测性能优势，提出阻尼累加离散灰色预测（DADGM）利用阻尼趋势参数减缓预测过程数据变化趋势，有效提高了灌溉系统稳定性和控制精度。构建FPID、NVUFP、DGM-NVUFP和DADGM-SVUFP四个控制模型实施水肥灌溉控制仿真试验，结果表明DADGM-SVUFP与其他模型相比稳态误差最优，调节时间比NVUFP、DGM-NVUFP分别少3.75 s、1.29 s，超调量比NVUFP、DGM-NVUFP分别降低9.2%、5.4%。灌溉测试进一步验证基于DADGM-SVUFP的智能灌溉系统适应性好、响应迅速、控制精度高，控制效果和系统稳定性均优于其他模型，能够满足水肥气灌溉系统的智能决策和精准控制。

Smith predictive intelligent irrigation system based on damping accumulated discrete grey prediction

The irrigation system has the characteristics of nonlinearity, multi disturbance and time lag，in order to achieve intelligent decision making and accurate irrigation of the irrigation system, a Smith predictive variable universe fuzzy PID irrigation control model based on damping accumulated discrete grey prediction is proposed. Aiming at the shortcomings of fuzzy PID controller model, such as low control accuracy and weak adaptability, the exponential function expansion factor is designed to adaptively adjust the variable universe, and the Smith predictive compensator is used to eliminate the influence of time lag, so as to improve the adaptability and robustness of irrigation control system. Combined with the prediction performance advantages of DGM and DAGM, DADGM is proposed to use damping trend parameters to slow down the change trend of process data, which effectively improves the stability and control accuracy of the irrigation system. Four control models of FPID, NVUFP, DGM-NVUFP and DADGM-SVUFP are constructed for irrigation simulation experiments. The results show that the steady state error of DADGM-SVUFP is the best compared with other models，the settling time is 3.75 s and 1.29 s less than NVUFP and DGM-NVUFP, and the overshoot is 9.2% and 5.4% lower than NVUFP and DGM-NVUFP respectively. The irrigation test further verifies that the intelligent irrigation system based on DADGM-SVUFP has good adaptability, rapid response and high control accuracy. The control effect and system stability are better than other models, which can meet the intelligent decision making and accurate control of the ox fertigation system.