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For first order plus dead time models, an optimal method for tuning PI controllers is presented using dimensional analysis and numerical optimisation techniques. Considering a step change in setpoint, optimal equations for determining PI parameters are obtained through minimising the integral of absolute error (IAE). The optimisation process is constrained to guarantee a minimum Gain margin (G.M.)...
The problem of model-based fault detection in the presence of both parametric uncertainty and noise is addressed in this paper. Intervals are used to represent the uncertainty in the system parameters and interval extensions of parity equations are used as adaptive threshold selectors. A proper combination in time of different (interval) parity equations, together with a robust indicator, is used...
Within TEAM [1] framework, which is an EU research project that envisions an integrated mobility system, where travellers, drivers, vehicles and the infrastructure construct a seamless and sustainable collaborative network, the Collaborative Public Transport Optimisation (CPTO) application is being developed. The main goal of the CPTO application is to improve the flexibility of the transport infrastructure...
The problem of observer design for robust residual generation in nonlinear discrete-time systems is considered. The method is proposed to solve this problem involving nonlinear time-dependent transformation of state-space system model into strict feedback form. To make this transformation practicable, algebra of time-dependent functions is developed.
New algorithms are presented for the computation of good upper and lower bounds on the structured singular value μ, for high order plants subject to purely real or mixed real/complex uncertainty. A geometric form of the Hahn-Banach theorem is used to develop an algorithm for computing an upper bound on μ, involving a linear program and a symmetric eigenvalue problem at each iteration. A proof of convergence...
The majority of renewable energy sources are non-dispatchable, meaning that it is not possible to control when and how much power they produce. For non-dispatchable renewable energy sources to meet a greater proportion of global electricity demand, the industry must develop and implement strategies that directly address the intermittency challenge. This paper considers electrical storage and transmission...
This paper discusses a knowledge-base encoding methodology for diagnostic tasks. In particular, it transforms fuzzy rules, provided by human experts, into algebraic equalities and inequalities. In this way, the “possible” disorders are the solution of a constraint satisfaction problem. If the disorders are weighted by some a priori possibility assertions (also provided by the experts), then the problem...
In this paper, we investigate the design of stationary ESSs based on supercapacitors (SCs) for metro network (MN). We implement a simulation tool in order to estimate the power flow among the metro vehicles and the ESSs through the MN. A new formulation of the ESSs siting and sizing optimisation problem is proposed and solved using particle swarm algorithm. The optimisation process minimises the energy...
In this paper, we investigate the performances of two different algorithms for calculating the metro vehicles speed profiles minimizing the energy consumption of a given path. The optimization problem, formulated as a Mixed-Integer Nonlinear Programming (MINLP) problem, take into account constraints related to the trip (time-table, distances, acceleration limits, etc.) and constraints related to the...
This paper intends to demonstrate use of Genetic Algorithm for solving fractional programming and which can be extended for DEA. Genetic Algorithm is one of the non-traditional algorithms for solving optimization problems. The multivariable fraction may have multiple optimum points. Genetic algorithm does not run the risk of getting trapped into the local minimum or maximum. The traditional optimization...
The present work describes the production of the ultrapure water using Continuous Electro-deionization (CEDI) method. The CEDI unit consist of ion exchange membranes, Mixed Bed-12 (MB-12) ion exchange resin and electrodes to remove ion impurities from feed water. The product water from the RO unit is supplied to the CEDI unit. The Quality of the ultra-pure water is determined by the amount of ions...
In the present work, Particle swarm optimisation (PSO) based Tsallis entropy method is employed to segment the buried object SONAR images. This SONAR detects the objects present beneath the seabed in ocean. Objects may be pipelines, and unexploded ordinances buried beneath the seabed. Computer vision for object detection is required when SONAR is equipped in autonomous underwater vehicle. The vehicle...
This study presents a tool for solving the Optimal Power Flow (OPF) problem in mixed Direct Current (DC) and Alternating Current (AC) systems. It allows to analyse the optimal operation of multiple independent systems, DC connected and linked to the AC system, from a steady state point of view and for several objective functions. The tool, implemented through implemented through MATLAB® Optimization...
Low frequency AC (LFAC) provides an alternative to HVDC and HVAC connections for offshore wind farms. Charging current is reduced as compared to standard 50Hz or 60Hz transmission and cable length thus may be extended. LFAC links to wind farms may be interconnected to form an offshore network - a significant advantage over HVDC technology which currently lacks a matured circuit breaker technology...
A novel single-channel blind source separation (SCBSS) algorithm using Cochleagram-mask based technique is presented in this paper. The proposed system offers benefits such as resemblance of a stereo signal concept given by one microphone, independent of initialization and a priori knowledge of the sources, improved performance with sources which do not strictly satisfy the windowed-disjoint orthogonality...
Positron annihilation is a well-established technique for producing spectra which can be analyzed for extracting physically meaningful parameters that characterize material defects and vacancies on an atomic scale. Mathematically, this is based on fitting a parameter-dependent model to the experimental data. Traditionally, this fit involves local nonlinear optimization routines that depend on a reasonable...
For the status that researches on customers' utility merely take up a small proportion in the studies on the cloud resource allocation, this paper proposes a cloud allocation model borrowing the idea of Network Utility Maximization(NUM)model, which maximizes the customers' utility. The model can be simplified to the Lagrangian dual function by the Lagrange function. Finally, a fuzzy subgradient algorithm...
To make full use of the characteristics of LDPC decoding, Stephan ten Brink had proposed a joint iterative demapping and decoding algorithm for LDPC coded BICM systems. Based on Brink proposed algorithm, we propose a modified joint iterative scheme to further reduce the computation complex. Different from the algorithm presented by Brink, in the process of iterative demapping and decoding, the proposed...
In this paper, we tackle with indefinite kernels by introducing projection matrix to formulate a positive semidefinite kernel. The projection matrix has a nice property of sharing the same set of eigenvectors with the original kernel. The proposed model can be regarded as a generalized version of spectrum method (denoising method and flipping method) by varying parameter λ. The problem of selecting...
As a common task in the fields of bioinformatics, enrichment analysis aims to investigate the functional association between a gene list of interest which often derived from biological experiments, and specific gene sets in a large database. The core problem of enrichment analysis can be characterized as a two-objective optimization problem. In this paper, we formulated the multiple gene sets enrichment...
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