Sliding mode approach to congestion control in connection-oriented communication networks

In this paper, a novel sliding mode flow controller design for the connection-oriented communication networks is proposed. The networks are modeled as discrete time systems with the available bandwidth acting as disturbance. The proposed controller is designed in such a way that the closed-loop system stability and fast, finite time error convergence are ensured. In order to avoid the problem of excessive control signal magnitude, a sliding mode controller with saturation is proposed. When this controller is applied no bottleneck link buffer overflow and full utilization of its available bandwidth are guaranteed. Furthermore, transmission rates generated by the controller are always upper bounded and nonnegative

On-demand Multipath Routing Protocols for Mobile Ad-Hoc Networks: A Comparative Survey

A Mobile Ad Hoc Network (MANET) is an infrastructure-less, self-organized and multi-hop network with a rapidly changing topology causing the wireless links to be broken at any time. Routing in such a network is challenging due to the mobility of its nodes and the challenge becomes more difficult when the network size increases. Due to the limited capacity of a multi-hop path and the high dynamics of wireless links, the single-path routing approach is unable to provide efficient high data rate transmission in MANETs. The multipath routing is the routing technique of using multiple alternative paths through a network. Furthermore, whenever a link failure is detected on a primary route, the source node can select the optimal route among multiple available routes. Therefore, the multipath routing approach is broadly utilized as one of the possible solutions to overcome the single-path limitation. Most of the multipath routing protocols are based on Ad Hoc On-Demand Distance Vector (AODV). The objective of this paper is to provide a survey and compare sets of multipath routing protocols for mobile ad-hoc networks. This survey will motivate the design of new multipath routing protocols, which overcome the weaknesses identified in this paper

DSOGI-PLL based power control method to mitigate control errors under disturbances of grid connected hybrid renewable power systems

The control of power converter devices is one of the main research lines in interfaced renewable energy sources, such as solar cells and wind turbines. Therefore, suitable control algorithms should be designed in order to regulate power or current properly and attain a good power quality for some disturbances, such as voltage sag/swell, voltage unbalances and fluctuations, long interruptions, and harmonics. Various synchronisation techniques based control strategies are implemented for the hybrid power system applications under unbalanced conditions in literature studies. In this paper, synchronisation algorithms based Proportional-Resonant (PR) power/current controller is applied to the hybrid power system (solar cell + wind turbine + grid), and Dual Second Order Generalized Integrator-Phase Locked Loop (DSOGI-PLL) based PR controller in stationary reference frame provides a solution to overcome these problems. The influence of various cases, such as unbalance, and harmonic conditions, is examined, analysed and compared to the PR controllers based on DSOGI-PLL and SRF-PLL. The results verify the effectiveness and correctness of the proposed DSOGI-PLL based power control method

Flow control in connection-oriented networks: a time-varying sampling period system case study

summary:In this paper congestion control problem in connection-oriented communication network with multiple data sources is addressed. In the considered network the feedback necessary for the flow regulation is provided by means of management units, which are sent by each source once every M data packets. The management units, carrying the information about the current network state, return to their origin round trip time RTT after they were sent. Since the source rate is adjusted only at the instant of the control units arrival, the period between the transfer speed modifications depends on the flow rate RTT earlier, and consequently varies with time. A new, nonlinear algorithm combining the Smith principle with the proportional controller with saturation is proposed. Conditions for data loss elimination and full resource utilisation are formulated and strictly proved with explicit consideration of irregularities in the feedback information availability. Subsequently, the algorithm robustness with respect to imprecise propagation time estimation is demonstrated. Finally, a modified strategy implementing the feed-forward compensation is proposed. The strategy not only eliminates packet loss and guarantees the maximum resource utilisation, but also decreases the influence of the available bandwidth on the queue length. In this way the data transfer delay jitter is reduced, which helps to obtain the desirable Quality of Service (QoS) in the network

Simulation model of a twin-tail, high performance airplane

The mathematical model and associated computer program to simulate a twin-tailed high performance fighter airplane (McDonnell Douglas F/A-18) are described. The simulation program is written in the Advanced Continuous Simulation Language. The simulation math model includes the nonlinear six degree-of-freedom rigid-body equations, an engine model, sensors, and first order actuators with rate and position limiting. A simplified form of the F/A-18 digital control laws (version 8.3.3) are implemented. The simulated control law includes only inner loop augmentation in the up and away flight mode. The aerodynamic forces and moments are calculated from a wind-tunnel-derived database using table look-ups with linear interpolation. The aerodynamic database has an angle-of-attack range of -10 to +90 and a sideslip range of -20 to +20 degrees. The effects of elastic deformation are incorporated in a quasi-static-elastic manner. Elastic degrees of freedom are not actively simulated. In the engine model, the throttle-commanded steady-state thrust level and the dynamic response characteristics of the engine are based on airflow rate as determined from a table look-up. Afterburner dynamics are switched in at a threshold based on the engine airflow and commanded thrust

A passivity based control methodology for flexible joint robots with application to a simplified shuttle RMS arm

The main goal is to develop a general theory for the control of flexible robots, including flexible joint robots, flexible link robots, rigid bodies with flexible appendages, etc. As part of the validation, the theory is applied to the control law development for a test example which consists of a three-link arm modeled after the shoulder yaw joint of the space shuttle remote manipulator system (RMS). The performance of the closed loop control system is then compared with the performance of the existing RMS controller to demonstrate the effectiveness of the proposed approach. The theoretical foundation of this new approach to the control of flexible robots is presented and its efficacy is demonstrated through simulation results on the three-link test arm

Expert systems for automated maintenance of a Mars oxygen production system

A prototype expert system was developed for maintaining autonomous operation of a Mars oxygen production system. Normal operation conditions and failure modes according to certain desired criteria are tested and identified. Several schemes for failure detection and isolation using forward chaining, backward chaining, knowledge-based and rule-based are devised to perform several housekeeping functions. These functions include self-health checkout, an emergency shut down program, fault detection and conventional control activities. An effort was made to derive the dynamic model of the system using Bond-Graph technique in order to develop the model-based failure detection and isolation scheme by estimation method. Finally, computer simulations and experimental results demonstrated the feasibility of the expert system and a preliminary reliability analysis for the oxygen production system is also provided

Home energy management systems regression models

Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáRegression Models have good use in the predictability of electrical systems and for Home Energy Management Systems (HEMS) buildings. This master’s thesis performs simulations with data from the Silk House, a building in Bragança. The objective is to determine better parameters in building data collection to improve its efficiency. Several Regression Models in Machine Learning (ML) are in a Python algorithm that constructs different inputs to an output. The Data Set is short, with seven scalar variables of the building’s power flow over a year, measured daily. The algorithm changed the number of variables chosen in the input and ran several models, with and without Principal Component Analysis (PCA). The Coefficient of Determination (R2) measures how well a regression model fits the data and its percentage of results withR2 in the range [0.75, 1] across all simulations. The best results for R2 in the range [0.75, 1] found 45% without PCA and 47.14% with PCA. With just one input, all models initially found 0% R2 in the range [0.75, 1]. The results of R2 in the range [0.75, 1] increased directly with more variables in the input. The variables with the best results were Photovoltaic Production (PP) and Direct Consumption (DC), being consistent with the profile of the building (office), which recommends its expansion. The variable Battery Charge (BC) never reached any R2 in the range [0.75, 1], which indicates possible suppression. It is also concluded that it is prudent to have more data and that non-linear tools are more suitable for site analysis.Os modelos de regressão possuem bom uso na previsibilidade de sistemas elétricos e em Home Energy Management Systems (HEMS). Esta dissertação de mestrado realiza simulações com dados da Silk House, edifício em Bragança. O objetivo é determinar melhores parâmetros na coleta de dados do edifício para melhorar sua eficiência. Os diversos algoritmos Regression Models em Machine Learning (ML) estão escritos em Python que constrói diferentes entradas para uma saída. O Data Set é curto, com sete variáveis escalares do trânsito de potência do edifício durante um ano, medidas diariamente. O algoritmo alterou o número de variáveis escolhidas na entrada e executou diversos modelos, com e sem Principal Component Analysis (PCA). O Coeficiente de Determinação R2 mede quão bem um modelo de regressão se ajusta aos dados e sua porcentagem de resultados com R2 na faixa [0, 75, 1] perante todas simulações. Os melhores resultados para R2 na faixa [0, 75, 1] encontraram 45% sem PCA e 47,14% com PCA. Com apenas uma entrada, todos os modelos encontraram inicialmente 0% R2 no intervalo [0, 75, 1]. Os resultados de R2 no intervalo [0, 75, 1] aumentaram diretamente com mais variaveis na entrada. As variáveis com melhores resultados foram Photovoltaic Production (PP) e Direct Consumption (DC), sendo condizentes com o perfil da edificação (escritório), o que recomenda sua expansão. A variável Battery Charge (BC) nunca atingiu nenhum R2 no intervalo [0.75, 1], o que indica possível supressão. Conclui-se também que é prudente ter mais dados e que as ferramentas não lineares são mais adequadas a análise do local