基于变论域模糊理论的温室番茄智能控温策略

为了对北方温室番茄种植进行精准的温度控制,根据番茄各生长时期的温度特性,运用温度积温理论以及变论域模糊控制理论提出了符合北方温室番茄种植的智能温度控制策略。利用温度积温法对温度阈值进行计算使其可以适应外界环境的动态变化,通过变论域模糊控制理论解决传统模糊控制方式因结构参数相对固定而不适用于高精度控制的难题,提升了稳定性以及系统的响应时间,降低了控制误差。仿真实验表明,该温度控制策略相比PID控制,在响应时间及超调量方面有54.17%和75%的提升;相比传统模糊控制,在响应时间及超调量方面有35.29%和55.56%的提升。温室实验表明,与原有控制策略相比,在日间与夜间控制方面,使用该控制策略的室内平均温度均更接近于期望温度值,同时节约近10%的能量消耗,有效提高能源利用率。

Temperature Control Strategy Based on Variable Universe Fuzzy Control Theory for Greenhouse Tomato Cultivation

In order to control accurately the temperature in tomato grown greenhouse in northern China, this study put forward the intelligent temperature control strategy, according to temperature characteristics for each period of tomato growth in greenhouse, using accumulated temperature theory and variable universe fuzzy control theory. Through accumulated temperature method to calculate temperature thresholds, this paper made it adapt to the dynamic changes in external environment, and solved the difficult problem in traditional fuzzy control method by the variable universe fuzzy control theory, due to its structural parameters of relative fixation, yet not applying to high-precision control. Thus, the stability and system response time were greatly enhanced, and the control error was reduced. The simulation results showed that compared to the PID control scheme, this method had a 54.17% and 75% improvement in response time and overshoot aspect. Compared with the traditional fuzzy control scheme, this methods in response time and overshoot aspect had 35.29% and 55.56% improvement. The actual effect of the test showed that compared with the existing control strategies, both in daytime and nighttime, this control strategy could make the average indoor temperature closer to the desired temperature value, and at the same time save nearly 10% energy consumption, thus effectively improved the energy utilization rate.