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• W2770944181 abstract "Extension of the storage life of high value horticultural produce is sought to allow sea freight access to lucrative overseas markets. Currently commercial storage technologies include the use of cold storage and controlled atmosphere (C.A.) storage, both of which endeavour to maintain the storage environment at some predetermined state. The set storage conditions are chosen using the criterion that the internal biological processes should be minimised over the storage period to maximise storage life. Advantage is sought over these conventional methods by using a machine to monitor the produce behaviour in response to the current storage conditions and to continually manipulate those conditions to minimise the life processes - quantified by the amount of carbon dioxide respired by the produce - without stopping them altogether.Due to the complexity, transience and largely unknown nature of the biological processes involved, to achieve such control over these requires the development and application of a novel control strategy. To meet this end, a control scheme is developed which is able to control a generic multiple input single output (M.I.S.O.) nonlinear process. Further, it is able to meet generic control objectives, that is, other than conventional set point control. Using an estimation of the conditional expectation of the system output derived from accumulated system inputs and output measurements, this CondEx controller, developed for single input single output (S.I.S.O.) systems by Black [1], learns the process behaviour without the guidance of a priori knowledge in model or structure form. Developments herein circumvent problems cited by Black and counter the 'curse of dimensionality' brought on by M.I.S.O. processes. Analysis of this controller also sheds light on the fundamental nature of control and has provided a basis for comparing different control strategies.To evaluate CondEx control in application to respiration control and to speed its development, both experimental and simulation platforms are presented. The latter is provided by the development of a unique computational dynamical model of the respiration behaviour of stored horticultural produce in response to its storage conditions, in particular, temperature and carbon dioxide and oxygen concentrations. The model parameters are determined using global optimisation techniques by the comparison of the model response with experimental time series data.The experimental apparatus used is also described. The Pneumeral research system both provides the data for model validation and allows computer monitoring and control of the storage environment in a 600 ml prototype storage container. Due to instrumentation limitations, experimental attention is restricted to asparagus because of its high rate of carbon dioxide production.Controller configurations for this application are developed and tested both in simulation and on asparagus respiration. This type of control is shown to be feasible and directions for future development are identified." @default.
• W2770944181 created "2017-12-04" @default.
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• W2770944181 date "2017-08-09" @default.
• W2770944181 modified "2023-09-25" @default.
• W2770944181 title "Optimal control for the storage of horticultural produce" @default.
• W2770944181 doi "https://doi.org/10.14264/uql.2017.736" @default.
• W2770944181 hasPublicationYear "2017" @default.
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