Three Time-Scale Digital Optimal Receding Horizon Control of the Climate in a Greenhouse with a Heat Storage Tank

Willigenburg, L.G. van; Henten, E.J. van; Meurs, W.Th.M. van

doi:10.1016/s1474-6670(17)40904-9

Cited by 10 publications

(7 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…That is also why these bounds are treated as hard constraints in the optimal control algorithm. The sampling interval of the control input u in the control horizon H is set to 20 min to increase the sensitivity of the control objective to control inputs in the first sampling interval [30].…”

Section: Control Algorithmmentioning

confidence: 99%

“…As this paper deals with different time-scales and the computation time, a summary of different durations of time is shown in Table 5. The growing period of 50 days was fixed in this research because scheduling arrangements concerning the delivery of lettuce to sellers or customers generally demand a fixed harvest time [30]. The 2 h sampling interval of the weather data in open-loop simulations was smoothed from the collected weather data to cut down on computation load [27].…”

Section: Summary Of Timementioning

confidence: 99%

See 1 more Smart Citation

Closed-Loop Optimal Control of Greenhouse Cultivation Based on Two-Time-Scale Decomposition: A Simulation Study in Lhasa

Dai

et al. 2022

Agronomy

View full text Add to dashboard Cite

Due to the heavy computation load of closed-loop simulations, optimal control of greenhouse climate is usually simulated in an open-loop form to produce control strategies and profit indicators. Open-loop simulations assume the model, measurements, and predictions to be perfect, resulting in too-idealistic indicators. The method of two-time-scale decomposition reduces the computation load, thus facilitating the online implementation of optimal control algorithms. However, the computation time of nonlinear dynamic programming is seldom considered in closed-loop simulations. This paper develops a two-time-scale decomposed closed-loop optimal control algorithm that involves the computation time. The obtained simulation results are closer to reality since it considers the time delay in the implementation. With this algorithm, optimal control of Venlo greenhouse lettuce cultivation is investigated in Lhasa. Results show that compared with open-loop simulations, the corrections in yield and profit indicators can be up to 2.38 kg m−2 and 11.01 CNY m−2, respectively, through closed-loop simulations without considering the computation time. When involving the time delay caused by the computation time, further corrections in yield and profit indicators can be up to 0.1 kg m−2 and 0.87 CNY m−2, respectively. These conservative indicators help investors make wiser decisions before cultivation. Moreover, control inputs and greenhouse climate states are within their bounds most of the time during closed-loop simulations. This verifies that the developed algorithm can be implemented in real time.

show abstract

Section: Control Algorithmmentioning

confidence: 99%

Section: Summary Of Timementioning

confidence: 99%

Closed-Loop Optimal Control of Greenhouse Cultivation Based on Two-Time-Scale Decomposition: A Simulation Study in Lhasa

Dai

et al. 2022

Agronomy

View full text Add to dashboard Cite

show abstract

“…For instance, Van Henten proposed a modified steepest ascent algorithm and used a forth order Runge-Kutta integration algorithm to obtain the numerical solution for optimal control trajectories [3]. An indirect gradient method was proposed which has proven its effectiveness in optimal greenhouse control and many other fields [5,20]. The search procedure to find optimal value is described as the following: The above feedback loop is repeated until the objective function value converges on the optimum .Since the simulation model runs independently from the optimization algorithm, there are in principle no restrictions with respect to its structure.…”

Section: Optimization Algorithmmentioning

confidence: 99%

Crop Model-Based Greenhouse Optimal Control System: Survey and Perspectives

Dong

Yang

et al. 2013

Computer and Computing Technologies in Agriculture VI

View full text Add to dashboard Cite

International audienceA survey is presented of the developments in scientific literature on the greenhouse optimal control. The related problems to optimal control were discussed, and the schematic diagram of optimal control system, combined crop models and optimization algorithm were covered focusing on issues such as: model simplification and validation, definition of objective function, input or output constraints and dynamic optimization, and especially structure-function Greenlab model was made s a first exploration for the optimal control application. Not only the above research issues were listed in the paper, the perspectives and the solutions are presented as well. It is pointed out that only the crop growth model is integrated into the greenhouse climate optimal control, the best economical result and energy-saving can be warranted

show abstract

“…Optimization of energy systems in greenhouse horticulture was studied before (e.g. Van Willigenburg et al (2000); Tap (2000); Van Ooteghem (2007b); Bozchalui and Cañizares (2014); Husmann and Tantau (2001); Vanthoor (2011); ), but the focus was mainly on greenhouse climate management and control. In those studies, a crop model is needed, and the operation of equipment is an integral part of the optimization and does often not comply with current practice.…”

Section: Stagementioning

confidence: 99%

“…Van Ooteghem (2007b) presented a (receding horizon) optimal control formulation for a semi-closed greenhouse with aquifer thermal storage and a boiler. Van Willigenburg et al (2000) proposed a three time-scale receding horizon optimal control approach to optimize a greenhouse with heat storage tank. In these examples only a limited set of equipment was considered, not fully reflecting the wide range of equipment available to greenhouse industry today.…”

Section: Introductionmentioning

confidence: 99%

Optimal management of energy resources in greenhouse crop production systems

Beveren¹

View full text Add to dashboard Cite

2 Minimal heating and cooling in a modern rose greenhouse 133 Optimal control of greenhouse climate using minimal energy and grower defined bounds 454 Optimal utilization of a boiler, combined heat and power installation, and heat buffers in horticultural greenhouses 715 Optimal utilization of energy equipment in a semi-closed greenhouse 107 Conclusion and discussion 143Summary 153Samenvatting 157Acknowledgments 161References 163 Curriculum Vitae 177List of Publications 178 PE&RC PhD Training Certificate 180Chapters 2, 3, 4, and 5 have been published as a journal article, as indicated on the first page of each chapter. Except for a different font, the addition of chapter-based numbering, and the addition of extra information in the footnotes (explicitly stated), the text of the manuscripts was integrally adopted and maintained throughout this thesis. Citations should be made to the original published article(s).

show abstract

Three Time-Scale Digital Optimal Receding Horizon Control of the Climate in a Greenhouse with a Heat Storage Tank

Cited by 10 publications

References 3 publications

Closed-Loop Optimal Control of Greenhouse Cultivation Based on Two-Time-Scale Decomposition: A Simulation Study in Lhasa

Closed-Loop Optimal Control of Greenhouse Cultivation Based on Two-Time-Scale Decomposition: A Simulation Study in Lhasa

Crop Model-Based Greenhouse Optimal Control System: Survey and Perspectives

Optimal management of energy resources in greenhouse crop production systems

Contact Info

Product

Resources

About