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In this study, we propose a novel controller architecture and design for the automatic control of agricultural mobile robots to be used in farms and greenhouses. There are two novelties of this study. The first novelty is a completely new type of controller architecture proposed in which reference inputs and measured outputs are fed separately independent from each other to the controller. The controller architecture currently used in the literature uses only the difference between reference and measurement which is the error signal. The proposed architecture in this study is completely novel in the sense that not only the error information is used in the controller but also the information in reference inputs and information in measured outputs are used separately. This means a completely new type of look to control system by utilizing the information maximally in order to achieve superior performance. This performance boost is shown in the paper where the proposed architecture achieves up to 2000% better performance compared with state-of-the-art controllers. Second, controller architecture is grown to a complex structure from an initially simple PID structure. Using the maximal information comes with the cost of computational complexity to design the controller. The second novelty of growing the controller from initially simple PID equivalent controller tackles this difficulty by making the problem tractable and efficient to compute. This way the proposed novel controller can be designed within minutes in a commercially available laptop computer. The proposed controller is tested on a simulated agricultural mobile robot and results are compared with a previous state-of-the-art optimal controller. It is believed that the proposed architecture will be dominant in future automatic controllers and make current state-of-the-art controllers obsolete. This is because of the full utilization of information in controller design which results in robust disturbance rejection performance. [ABSTRACT FROM AUTHOR]

This study explores the optimization of kinetic facades to promote environmental sustainability in building designs, addressing the critical issues of high energy consumption and CO2 emissions prevalent in the construction sector. The focus is on achieving an intricate balance between maximizing natural daylight and minimizing solar radiation using innovative kinetic facade designs. Parametric modeling tools are utilized in the design process to experiment with various facade configurations. The effectiveness of these designs is then validated using both digital and physical prototypes, with their adaptability to diverse climatic conditions evaluated through dynamic simulations. A key component of the study is the application of the Wallacei plugin for Grasshopper, which assists in multi-objective optimization to determine the most effective facade aperture ratios. The results demonstrates a substantial reduction in solar radiation levels, with a 70% decrease on the first floor and a 76% decrease on the seventh floor, achieved by optimizing aperture ratios. The study concludes that optimizing kinetic facades significantly improves building performance compared to traditional glass facades, offering an effective balance between daylight enhancement and solar radiation reduction, influenced by seasonal changes. It also emphasizes the importance of factors such as building height and the surrounding environment in facade design. Overall, the findings highlight kinetic facades as a viable solution for improving building efficiency and occupant comfort, suggesting a promising avenue for advancements in architectural design and construction. [ABSTRACT FROM AUTHOR]