温室温度精确反馈线性化预测控制
|
摘要
温室温度系统具有强非线性特性,通常会导致模型预测控制算法操作复杂,不适宜实际生产应用。针对此问题,提出了基于输入输出精确线性化的温度预测控制算法。根据能量平衡定律,构建了温室温度系统机理模型,将其转换为仿射非线性系统;利用微分几何理论,获得非线性状态反馈控制律,实现了原系统输入输出的精确线性化;在此线性化系统的基础上,设计了预测控制器,使温度跟踪误差与加热损耗的加权和达到最小。仿真结果表明:精确反馈线性化预测控制系统能够综合权衡控制精度与运行能耗,调控效果良好。
Greenhouse temperature system is highly non-linear. The problem of model predictive controller design becomes very complex and the online computational demands are great,which limit the practical applications. To solve the problem,the design of greenhouse temperature predictive control with input-output accuracy linearization is presented.According to the law of conservation of energy,the greenhouse temperature physical model is described. Then the model is transferred to an affine non-linear system. Based on the differential geometry theory,the feedback control law is derived and is used to achieve the input-output accuracy linearization of the original system. On the basis of the linearized system,the predictive control strategy is designed to minimize the weighted sum between set point tracking deviation and heating energy consumption during the control process. The simulation results indicate that the proposed predictive control with accuracy feedback linearization can find a trade-off between control precision and cost requirements and that it can contribute to a good control performance.
Greenhouse temperature system is highly non-linear. The problem of model predictive controller design becomes very complex and the online computational demands are great,which limit the practical applications. To solve the problem,the design of greenhouse temperature predictive control with input-output accuracy linearization is presented.According to the law of conservation of energy,the greenhouse temperature physical model is described. Then the model is transferred to an affine non-linear system. Based on the differential geometry theory,the feedback control law is derived and is used to achieve the input-output accuracy linearization of the original system. On the basis of the linearized system,the predictive control strategy is designed to minimize the weighted sum between set point tracking deviation and heating energy consumption during the control process. The simulation results indicate that the proposed predictive control with accuracy feedback linearization can find a trade-off between control precision and cost requirements and that it can contribute to a good control performance.
引文
[1]Maher A,Kamel E,Enrico F,et al.An intelligent system for the climate control and energy savings in agricultural greenhouses[J].Energy Efficiency,2016,9(6):1241-1255.
[2]Montoya A P,Guzmán J L,Rodríguez F,et al.A hybridcontrolled approach for maintaining nocturnal greenhouse temperature:Simulation study[J].Computers&Electronics in Agriculture,2016,123:116-124.
[3]孔小兵,刘向杰.基于输入输出线性化的连续系统非线性模型预测控制[J].控制理论与应用,2012,29(2):217-224.
[4]Oliveira J B,Boaventura-Cunha J,Moura Oliveira P B.Afeasibility study of sliding mode predictive control for greenhouses[J].Optimal Control Applications&Methods,2016,37:730-748.
[5]Gruber J K,Guzmán J L,Rodríguez F,et al.Nonlinear MPC based on a Volterra series model for greenhouse temperature control using natural ventilation[J].Control Engineering Practice,2011,19(4):354-366.
[6]王向东,何南思.温室大棚温湿度跟踪切换最优控制器[J].沈阳工业大学学报,2014,36(5):543-549.
[7]乐江源,谢运祥,冀玉丕,等.CCM Buck变换器的精确反馈线性化滑模变结构控制[J].华南理工大学学报:自然科学版,2012,40(2):130-135.
[8]Gurban E H,Dragomir T L,Andreescu G D.Greenhouse climate control enhancement by using genetic algorithms[J].Control Engineering&Applied Informatics,2014,16(3):35-45.
[9]程文锋,杨祥龙,王立人.温室温湿度的反馈前馈线性化解耦控制[J].东南大学学报:自然科学版,2012,42(S1):5-10.
[10]Van Straten G,Van Henten E J,Van Willigenburg L G,et al.Optimal control of greenhouse cultivation[M].Boca Raton:CRC Press,2010:1-296.
[12]姚志迎.温室系统环境优化控制研究[D].北京:中国农业大学,2013.
[13]周岗,姚琼荟,陈永冰,等.基于输入输出线性化的船舶全局直线航迹控制[J].控制理论与应用,2007,24(1):117-121.
[14]González R,Rodríguez F,Guzmán J L,et al.Robust constrained economic receding horizon control applied to the two time-scale dynamics problem of a greenhouse[J].Optimal Control Applications&Methods,2014,35(4):435-453.
[15]陈俐均,杜尚丰,李嘉鹏,等.温室环境温度预测自适应机理模型参数在线识别方法[J].农业工程学报,2017,33(S1):315-321.
[16]Iliev O L,Sazdov P,Zakeri A.A Fuzzy Logic-Based Controller for Integrated Control of Protected Cultivation[J].Management of Environmental Quality an International Journal,2014,25(25):75-85.
[2]Montoya A P,Guzmán J L,Rodríguez F,et al.A hybridcontrolled approach for maintaining nocturnal greenhouse temperature:Simulation study[J].Computers&Electronics in Agriculture,2016,123:116-124.
[3]孔小兵,刘向杰.基于输入输出线性化的连续系统非线性模型预测控制[J].控制理论与应用,2012,29(2):217-224.
[4]Oliveira J B,Boaventura-Cunha J,Moura Oliveira P B.Afeasibility study of sliding mode predictive control for greenhouses[J].Optimal Control Applications&Methods,2016,37:730-748.
[5]Gruber J K,Guzmán J L,Rodríguez F,et al.Nonlinear MPC based on a Volterra series model for greenhouse temperature control using natural ventilation[J].Control Engineering Practice,2011,19(4):354-366.
[6]王向东,何南思.温室大棚温湿度跟踪切换最优控制器[J].沈阳工业大学学报,2014,36(5):543-549.
[7]乐江源,谢运祥,冀玉丕,等.CCM Buck变换器的精确反馈线性化滑模变结构控制[J].华南理工大学学报:自然科学版,2012,40(2):130-135.
[8]Gurban E H,Dragomir T L,Andreescu G D.Greenhouse climate control enhancement by using genetic algorithms[J].Control Engineering&Applied Informatics,2014,16(3):35-45.
[9]程文锋,杨祥龙,王立人.温室温湿度的反馈前馈线性化解耦控制[J].东南大学学报:自然科学版,2012,42(S1):5-10.
[10]Van Straten G,Van Henten E J,Van Willigenburg L G,et al.Optimal control of greenhouse cultivation[M].Boca Raton:CRC Press,2010:1-296.
[12]姚志迎.温室系统环境优化控制研究[D].北京:中国农业大学,2013.
[13]周岗,姚琼荟,陈永冰,等.基于输入输出线性化的船舶全局直线航迹控制[J].控制理论与应用,2007,24(1):117-121.
[14]González R,Rodríguez F,Guzmán J L,et al.Robust constrained economic receding horizon control applied to the two time-scale dynamics problem of a greenhouse[J].Optimal Control Applications&Methods,2014,35(4):435-453.
[15]陈俐均,杜尚丰,李嘉鹏,等.温室环境温度预测自适应机理模型参数在线识别方法[J].农业工程学报,2017,33(S1):315-321.
[16]Iliev O L,Sazdov P,Zakeri A.A Fuzzy Logic-Based Controller for Integrated Control of Protected Cultivation[J].Management of Environmental Quality an International Journal,2014,25(25):75-85.