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Abstract Due to the increasing application of unmanned aerial vehicles (UAVs), it is necessary to design new strategies related to the complexity of the maneuvering task of UAVs because it is sometimes necessary to avoid obstacles or to maneuver in reduced spaces. Sliding mode controllers (SMCs) have now become a superior alternative for tracking robotics and other types of mechanical systems. For this reason, this chapter proposes fast terminal SMCs for high speed and complex maneuvering of unmanned aerial vehicles. Three fast terminal SMC (FTSMC) techniques will be used for tracking UAVs at high speed. The first is a second-order FTSMC, taking into account the dynamics of UAVs in order to achieve efficient tracking when complex maneuvers are carried out at high speed. The second strategy will be an adaptive quick terminal backstepping SMC and the third strategy will be an adaptive second-order SMC. These three strategies will be designed with the Lyapunov approach, given that the sliding surface reach time is sufficiently small to improve the system's time response when high speed and complex maneuvering is required. Convergence of the sliding variables will be tested by numerical experiments and a comparative analysis will be carried out by implementing several reference complex trajectories. Finally, a discussion and conclusion section on future work is provided.

As we enter the 21st century, the sustainability of modern agricultural farming systems is being questioned. Historically, sustainability has been defined primarily in terms of profit, with less emphasis placed on ethical and environmental issues. It is increasingly apparent that for modern farming systems to be sustainable into the next century, they must not only be profitable, but also both ethically and environmentally sound. As a consequence of this shift in emphasis, the quality of products arising from the farming of animals is being more closely scrutinised by consumers.

ABSTRACT The ECLAM (Energy Carbon Land Allocations Model) is used to simulate the potential of forestry and bio-fuels (fuels derived from biological raw material) in climate change response. The intuition for this approach is that, in the short and medium term, there is little flexibility in the energy supply system owing to the long lifetime of typical energy sector fixed assets, whereas there is substantial flexibility in the allocation of land at least until global population growth leads to greater demands for land, for food and fibre production. Furthermore, the utilisation of land for energy production and for a medium term ‘buffer stock’ of carbon results in a flow of rents to landowners which can provide the capital needed for the more intensive agriculture that will be needed in the next century. The carbon flows related to absorption by forestry and biofuel production, and to emissions from burning fuel, together with the effects of natural absorption, combine to yield a time profile for atmospheric carbon. Simulations run on a global scale demonstrate the medium term use of plantation forestry as a buffer stock of carbon, for eventual use partly as fibre, and partly as fuel. Results are shown for the variables associated with the scenario like rent of land, productivity of agriculture and effects on the labour market. An important decrease of atmospheric CO2 is diagnosed to be possible by the described integrated ‘biofuels and sequestration strategy1.

Many lakes world-wide suffer from eutrophication as a result of high external nutrient inputs from domestic sewage, industry and agricultural activities. Increased demands for water by a growing and developing human population as well as enhanced global warming may escalate the eutrophication on a global scale in the next century. Yet, in some countries large efforts are now being made to combat eutrophication by reducing the phosphorus input. Some lakes respond rapidly to such loading reductions, while others are highly resistant due to high internal phosphorus loading (chemical resistance) or homeostatic effects of the food web altered by eutrophication (biological resistance). Some general models have been developed for the response of lakes to reduced loading, but major advances within this field can be expected in the future when more case studies appear. While these models may be used as a core for evaluating response patterns, local factors should always be considered to avoid wrong and often expensive decisions. To precipitate recovery from chemical and biological resistance, several physico-chemical and biological restoration methods have been developed. The biological methods include removal of planktivorous and benthivorous fish, stocking of piscivorous fish, protection or planting of submerged macrophytes, introduction of artificial structures, or addition of mussels. A widely applied method is removal of planktivorous and benthivorous fish. In many cases such efforts have yielded major improvements in water quality and the ecological state of the lakes. Yet, the listed restoration methods have mainly been applied to northern temperate lakes and cannot readily be transferred to subtropical and tropical lakes where the eutrophication-related problems are going to be greatest in the future. There is thus a major need for development and adaptation of methods focusing on south temperate, subtropical and tropical lakes.

This chapter describes the structure, datasets and processing methods of a new spatial analysis framework to assess the response of agricultural landscapes to climates and soils. Georeferenced gridded information on climate (historical and climate change scenarios), soils, terrain and crop management are dynamically integrated by a process-based biophysical model within a high-performance computing environment. The framework is used as a research tool to quantify productivity and environmental aspects of agricultural systems. An application case study using New Zealand spatial datasets and silage maize cropping systems illustrates the current framework capability and highlights key areas for enhancement in future gridded modelling research.

Precision agriculture has provided supporting applications for farmers with the use of Artificial Intelligence (AI) for processing farming data. Pastures are one of the main sources for dairy farming that have a great share in economy of agriculture. Weeds are the main issue of pastures, which impose a huge cost to dairy farmers annually. This paper proposes designing a software framework based on a fuzzy logic system for pasture assessment and pasture clean-up. Once weeds and empty spots of any pasture reduce its productivity, we considered them as two uncertainties that affect the weed management process. Applying our system to any pasture can measure the weed density and bareness through images and score the state of pasture’s productivity. With the aid of our software framework we can produce 2D weed density maps, 2D bareness maps, and scoring maps, which provide a better insight into the pastures. The types of 2D maps and the yield score can help and support dairy farmers to schedule, organize, and manage pastoral weeds.

In general, the increasing proportion of agriculture in a catchment parallels a decline in water quality. Farming systems, although optimized for profit, may not be optimized for a catchment's climate or physical geography resulting in losses of nutrients and sediment, key indicators of poor water quality. Strategies are available to mitigate these losses and should be chosen to fit the farm system and water quality objective. Globally, there are also many initiatives that aim to buffer the economic impact of changing management or strategies prescribed to reduce nutrient or sediment loss. However, care must be taken to fully assess the impact of land-use change or mitigation strategies within a catchment before policy is implemented, otherwise factors such as time lags may mean that water quality objectives will not be achieved.

We may now examine in more detail the causes of vegetation changes, chiefly through experiments or observations which ecologists have carried out on the redevelopment of forest vegetation in eastern North America after forest clearance. The examples, augmenting the information in Chapter 9, are used to identify some general principles.

Biological control of terrestrial weeds using insect herbivores has been practised in many countries throughout the world for nearly one and a half centuries. The first documented case was in the 1860s, when the cochineal insect Dactylopius ceylonicus (Green) was introduced from India into Sri Lanka, where it successfully controlled prickly pear cactus, Opuntia vulgaris Miller (Rao et al., 1971). The next programme, which began in 1902 with the release of 14 control agents for Lantana camara L., has continued intermittently from then until the present day, but has been nowhere near as successful as the Opuntia programme (Julien and Griffiths, 1998). Up until the end of 1996 there had been at least 1150 deliberate releases (including aquatic weeds) of 365 species of invertebrates and fungi onto 133 weed species in 75 countries (Julien and Griffiths, 1998). However, only 25 per cent of all releases made before 1985 contributed to control (Julien, 1989). Crawley (1989a) was not much more encouraging when he commented that’ the history of biological weed control is marked by a small number of spectacular successes and a large number of disappointments.’