Cross Entropy-based Analysis of Spacecraft Control Systems

Space missions increasingly require sophisticated guidance, navigation and control algorithms, the development of which is reliant on verification and validation (V&V) techniques to ensure mission safety and success. A crucial element of V&V is the assessment of control system robust performance in the presence of uncertainty. In addition to estimating average performance under uncertainty, it is critical to determine the worst case performance. Industrial V&V approaches typically employ mu-analysis in the early control design stages, and Monte Carlo simulations on high-fidelity full engineering simulators at advanced stages of the design cycle. While highly capable, such techniques present a critical gap between pessimistic worst case estimates found using analytical methods, and the optimistic outlook often presented by Monte Carlo runs. Conservative worst case estimates are problematic because they can demand a controller redesign procedure, which is not justified if the poor performance is unlikely to occur. Gaining insight into the probability associated with the worst case performance is valuable in bridging this gap. It should be noted that due to the complexity of industrial-scale systems, V&V techniques are required to be capable of efficiently analysing non-linear models in the presence of significant uncertainty. As well, they must be computationally tractable. It is desirable that such techniques demand little engineering effort before each analysis, to be applied widely in industrial systems. Motivated by these factors, this thesis proposes and develops an efficient algorithm, based on the cross entropy simulation method. The proposed algorithm efficiently estimates the probabilities associated with various performance levels, from nominal performance up to degraded performance values, resulting in a curve of probabilities associated with various performance values. Such a curve is termed the probability profile of performance (PPoP), and is introduced as a tool that offers insight into a control system's performance, principally the probability associated with the worst case performance. The cross entropy-based robust performance analysis is implemented here on various industrial systems in European Space Agency-funded research projects. The implementation on autonomous rendezvous and docking models for the Mars Sample Return mission constitutes the core of the thesis. The proposed technique is implemented on high-fidelity models of the Vega launcher, as well as on a generic long coasting launcher upper stage. In summary, this thesis (a) develops an algorithm based on the cross entropy simulation method to estimate the probability associated with the worst case, (b) proposes the cross entropy-based PPoP tool to gain insight into system performance, (c) presents results of the robust performance analysis of three space industry systems using the proposed technique in conjunction with existing methods, and (d) proposes an integrated template for conducting robust performance analysis of linearised aerospace systems

Conceptual study of Dooshivisha (Cumulative toxicity) w.r.t. Ancient classics and Modern science

Ayurveda describes the vast turnover of beauty aid products. More and more new synthetic substances are introduced every day. Many of these are not adequately tested for safety, in particular for routes other than oral or parenteral. Increased incidence of skin conditions like eczema and contact dermatitis after using newer cosmetics suggest that this may be due to local toxic effects or toxic effects manifested on this phenomenon as Dooshivisha. They are relevant to the current way of life considering the prevalence of pollution, occupational hazards and extent of exposure to toxins in food and other articles used in daily life. Present generation is much more likely to consume junk foods-cold drinks, to have unhealthy travelling habits, working late nights, working with computers in A.C rooms. This is referred to by terms like Hetusatatya, Vegavarodha, Diwaswapa, Viparit Chesta, Virudhannasevana which in turn hamper the normal physiology of human body. Same thing is mentioned in Ayurvedic texts also under the topic of Pradnyaparadh which is the basic cause for all diseases. This Pradnyaparadha is responsible to disturb the daily routine life and person has to face with the complaints of ill-health

Mathematical Tools for Irrigation Water Management An Overview

Irrigation water management has significant economic implications in developing countries like India. While the structural infrastructure has been created with a huge financial investment in these countries, it is vital that appropriate non-structural measures be adopted for efficient water management. Scientific policies of operation of irrigation reservoir systems need to be developed with the aid of mathematical tools and implemented in practice. In this paper, a brief overview of some mathematical tools for irrigation system operation, crop water allocations and performance evaluation is presented, with a discussion on the work carried out in India by the author’s team. Recent tools and techniques of fuzzy optimization and fuzzy inference systems that incorporate imprecision in management goals and constraints and that address the interests of stakeholders are also discussed. Perceptions on issues relating to applicability of the tools to real-life problems, existing gaps between theory and practice and possible hurdles in narrowing such gaps in developing countries are presented

Correction for Bias in Downscaling GCM Simulations for Hydrologic Impact Assessment

In a statistical downscaling model, it is important to remove the bias of General Circulations Model (GCM) outputs resulting from various assumptions about the geophysical processes. One conventional method for correcting such bias is standardisation, which is used prior to statistical downscaling to reduce systematic bias in the mean and variances of GCM predictors relative to the observations or National Centre for Environmental Prediction/ National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data. A major drawback of standardisation is that it may reduce the bias in the mean and variance of the predictor variable but it is much harder to accommodate the bias in large-scale patterns of atmospheric circulation in GCMs (e.g. shifts in the dominant storm track relative to observed data) or unrealistic inter-variable relationships. While predicting hydrologic scenarios, such uncorrected bias should be taken care of; otherwise it will propagate in the computations for subsequent years. A statistical method based on equi-probability transformation is applied in this study after downscaling, to remove the bias from the predicted hydrologic variable relative to the observed hydrologic variable for a baseline period. The model is applied in prediction of monsoon stream flow of Mahanadi River in India, from GCM generated large scale climatological data

Increasing frequency and spatial extent of concurrent meteorological droughts and heatwaves in India

The impacts of concurrent droughts and heatwaves could be more serious compared to their individual occurrence. Meteorological drought condition is generally characterized by low rainfall, but impact of such an event is amplified with simultaneous occurrence of heatwaves. Positive feedback between these two extremes can worsen the rainfall deficit situation to serious soil moisture depletion due to enhanced evapotranspiration. In this study, the concurrence of meteorological droughts and heatwaves is investigated in India using Indian Meteorological Department (IMD) high resolution gridded data over a period of 60 years. Significant changes are observed in concurrent meteorological droughts and heatwaves defined at different percentile based thresholds and durations during the period 1981-2010 relative to the base period 1951-1980. There is substantial increase in the frequency of concurrent meteorological droughts and heatwaves across whole India. Statistically significant trends in the spatial extent of droughts are observed in Central Northeast India and West Central India; however, the spatial extent affected by concurrent droughts and heatwaves is increasing across whole India. Significant shifts are identified in the distribution of spatial extent of concurrent drought and heatwaves in India compared to the base period

Urban Floods: Case Study of Bangalore

Bangalore is one of the fastest growing cities in India and is branded as ‘Silicon Valley of India’ for heralding and spearheading the growth of Information Technology (IT) based industries in the country. With the advent and growth of IT industry, as well as numerous industries in other sectors and the onset of economic liberalisation since the early 1990s, Bangalore has taken lead in service-based industries fuelling substantial growth of the city both economically and spatially. Bangalore has become a cosmopolitan city attracting people and business alike, within and across nations. This profile notes the urban setting and provides an overview of the urban fabric, while discussing various prospects related to infrastructure and governance (Sudhira, et al. 2007)

Fuzzy waste load allocation model: simulation-optimization approach

The problem of Waste Load Allocation (WLA) for water quality management of a river system is addressed with a simulation-optimization approach. The WLA model developed in the study provides the best compromise solutions to the Pollution Control Agency (PCA) responsible for maintaining the water quality and the dischargers disposing pollutants into the river system. A previously developed Fuzzy Waste Load Allocation Model (FWLAM) is extended to incorporate QUAL2E, a water quality simulation model developed by the U.S. Environmental Protection Agency for modeling the pollutant transport in a river. The imprecision associated with establishing water quality standards and the aspirations of the PCA and dischargers are quantified using fuzzy goals with appropriate membership functions. The membership functions of the fuzzy goals represent the variation of the goal satisfaction in the system. A Genetic Algorithim (GA) is used as an optimization tool to find optimal fraction removal levels to the dischargers and the corresponding satisfaction level. Because a GA is an unconstrained optimization tool, it is extended to handle constraints by complementing it with Homomorphous Mapping (HM), a constraint handling method for evolutionary algorithms. The GA directs the decision vector in an encoded form to HM. HM, after a few interactions with QUAL2E, redirects the decoded solution back to the GA. The GA assigns a fitness value to the feasible solution vector and applies operators to refine the solution. This interaction among the GA, HM and QUAL2E continues until a prespecified criterion for global optimality is met. Application of the model is illustrated with a case study of the Tunga-Bhadra River in South India

Hydrological status and outlooks

Chapter 6. Water is critical for the sustenance of livelihoods, economic and social development, and the natural environment. With many parts of the world experiencing more variable hydrological conditions and more severe, and more frequent extremes, water resources management is increasingly critical for human and environmental well-being (Kundzewicz & Matczak, 2015). Hydrological status and outlook systems make use of current, historic, and forecast hydro-meteorological data to appraise current hydrological status in relation to that localities “normal”. This indicates the status of water resources, as well as whether the area may be susceptible to drought or flooding in the near future. Sub-seasonal to seasonal forecasting then enables assessments of whether current conditions are likely to get better or worse over the coming weeks and months. In this chapter, hydrological status and outlooks systems are presented as a critical tool for the long-term management of water resources, as well as risk planning, in India