Particle Swarm Optimization—An Adaptation for the Control of Robotic Swarms

Particle Swarm Optimization (PSO) is a numerical optimization technique based on the motion of virtual particles within a multidimensional space. The particles explore the space in an attempt to find minima or maxima to the optimization problem. The motion of the particles is linked, and the overall behavior of the particle swarm is controlled by several parameters. PSO has been proposed as a control strategy for physical swarms of robots that are localizing a source; the robots are analogous to the virtual particles. However, previous attempts to achieve this have shown that there are inherent problems. This paper addresses these problems by introducing a modified version of PSO, as well as introducing new guidelines for parameter selection. The proposed algorithm links the parameters to the velocity and acceleration of each robot, and demonstrates obstacle avoidance. Simulation results from both MATLAB and Gazebo show close agreement and demonstrate that the proposed algorithm is capable of effective control of a robotic swarm and obstacle avoidance

Understanding the effects of drought upon carbon allocation and cycling in an Amazonian rain forest

Research Grant (NER/A/S/2003/1609)The Amazon rain forest plays an important role in regional and global biogeochemical cycling, but the region may undergo an increase in the frequency and severity of drought conditions driven by global climate change, regional deforestation and fire. The effects of this drought on carbon cycling in the Amazon, particularly below-ground, are potentially large but remain poorly understood. This thesis examines the impacts of seasonal and longer-term drought upon ecosystem carbon allocation and cycling at an Amazon rain forest site with a particular focus upon below-ground processes. Measurements are made at three one-hectare forest plots with contrasting soil type and vegetation structure, to observe responses across a range of Amazon primary forest types. A fourth plot is subjected to partial rainfall exclusion to permit measurement of forest responses to a wider range of soil moisture levels than currently exists naturally. An analysis of the number of samples required to accurately quantify important ecosystem carbon stocks and fluxes is used to guide the sampling strategy at the field site. Quantifying root dynamics, in particular, presents methodological challenges. Thus, I critically review existing methods, and develop techniques to accurately measure root standing biomass and production. Subsequently, these techniques are used to record root responses, in terms of standing biomass, production, morphology, turnover and nutrient content, to variation in soil moisture across the four rain forest plots. There is substantial environmental variation in root characteristics. However, several responses remain consistent across plots: root production of biomass, length, and surface area, is lower where soil is dry, while root length and surface area per unit mass show the opposite pattern. The other major component of the below-ground carbon cycle is soil carbon dioxide efflux. I partition this efflux, on each plot, into contributions from organic ground surface litter, roots and soil organic matter, and investigate abiotic and biotic causes for observed differences within and between plots. On average, the percentage contribution of soil organic matter respiration to total soil carbon dioxide efflux declines during the dry season, while root respiration contribution displays the opposite trend. However, spatial patterns in soil respiration are not directly attributable to variation in either soil moisture or temperature. Instead, ground surface organic litter mass and root mass account for 44 % of observed spatial heterogeneity in soil carbon dioxide efflux. Finally, information on below-ground carbon cycling is combined with aboveround data, of canopy dynamics and stem wood production and mortality, to analyze the potential effects of drought upon carbon cycling in an Amazon forest ecosystem. Comparison of the rainfall exclusion plot with a similar, but unmodified, control plot reveals potentially important differences in tree carbon allocation, mortality, reproduction, soil respiration and root dynamics. The apparent net consequence of these changes is that, under drier conditions, the amount of CO2 moving out of the forest and into the atmosphere is diminished. This synthesis of above-ground and below-ground data advances understanding of carbon cycling in rain forests, and provides information which should allow more accurate modelling of the response of the Amazon region to future drought. Additional measurements at other sites, and of other ecosystem carbon fluxes, should further refine modelling predictions

Checking Admissibility Using Natural Dualities

This paper presents a new method for obtaining small algebras to check the admissibility-equivalently, validity in free algebras-of quasi-identities in a finitely generated quasivariety. Unlike a previous algebraic approach of Metcalfe and Rothlisberger that is feasible only when the relevant free algebra is not too large, this method exploits natural dualities for quasivarieties to work with structures of smaller cardinality and surjective rather than injective morphisms. A number of case studies are described here that could not be be solved using the algebraic approach, including (quasi)varieties of MS-algebras, double Stone algebras, and involutive Stone algebras