Specialised branch-and-bound algorithm for transmission network expansion planning

An algorithm is presented that finds the optimal plan long-term transmission for till cases studied, including relatively large and complex networks. The knowledge of optimal plans is becoming more important in the emerging competitive environment, to which the correct economic signals have to be sent to all participants. The paper presents a new specialised branch-and-bound algorithm for transmission network expansion planning. Optimality is obtained at a cost, however: that is the use of a transportation model for representing the transmission network, in this model only the Kirchhoff current law is taken into account (the second law being relaxed). The expansion problem then becomes an integer linear program (ILP) which is solved by the proposed branch-and-bound method without any further approximations. To control combinatorial explosion the branch- and bound algorithm is specialised using specific knowledge about the problem for both the selection of candidate problems and the selection of the next variable to be used for branching. Special constraints are also used to reduce the gap between the optimal integer solution (ILP program) and the solution obtained by relaxing the integrality constraints (LP program). Tests have been performed with small, medium and large networks available in the literature.

Efficient linear programming algorithm for the transmission network expansion planning problem

The transmission network planning problem is a non-linear integer mixed programming problem (NLIMP). Most of the algorithms used to solve this problem use a linear programming subroutine (LP) to solve LP problems resulting from planning algorithms. Sometimes the resolution of these LPs represents a major computational effort. The particularity of these LPs in the optimal solution is that only some inequality constraints are binding. This task transforms the LP into an equivalent problem with only one equality constraint (the power flow equation) and many inequality constraints, and uses a dual simplex algorithm and a relaxation strategy to solve the LPs. The optimisation process is started with only one equality constraint and, in each step, the most unfeasible constraint is added. The logic used is similar to a proposal for electric systems operation planning. The results show a higher performance of the algorithm when compared to primal simplex methods.

A controller design used in Lorenz synchronization chaotic system for secure communication based on LMI fuzzy control system

This paper describes a mathematical study about chaotic system and about the unified approach of chaos control via fuzzy control system based in Linear Matrix Inequality to design a controller which synchronizes the transmission/reception system. This system, that was based in Lorenz chaotic circuit, can be used for transmit signals in secure way.

Optimal capacitor placement in radial distribution networks

The capacitor placement (replacement) problem for radial distribution networks determines capacitor types, sizes, locations and control schemes. Optimal capacitor placement is a hard combinatorial problem that can be formulated as a mixed integer nonlinear program. Since this is a NP complete problem (Non Polynomial time) the solution approach uses a combinatorial search algorithm. The paper proposes a hybrid method drawn upon the Tabu Search approach, extended with features taken from other combinatorial approaches such as genetic algorithms and simulated annealing, and from practical heuristic approaches. The proposed method has been tested in a range of networks available in the literature with superior results regarding both quality and cost of solutions.

Effect of Supragingival plaque control in smokers and never-smokers: 6-month evaluation of patients with periodontitis

Background: the effect of supragingival plaque control on clinical signs of periodontitis is controversial, particularly when smoking habits are considered. This study evaluated the clinical effects of supragingival plaque control on clinical signs of periodontitis in smokers and never-smokers.Methods: the following data were collected for 25 never-smokers and 25 smokers at baseline and 30, 90, and 180 days: visible plaque index (VPI), gingival bleeding index (GBI), bleeding on probing (BOP), periodontal probing depth (PD), and clinical attachment loss (CAL). After baseline examinations, supragingival scaling was performed. Oral hygiene practices were reinforced and reevaluated weekly during the experimental period. Linear models adjusted for clustering of observations within individuals were used for statistical analysis.Results: Reductions in VPI were significant for both groups, with no intergroup differences. GBI at baseline was similar between groups, and at 30, 90, and 180 days, smokers had a lower GBI than never-smokers. Significant reductions were observed in PD for shallow (1 to 3 mm), moderate (4 to 5 mm), and deep sites (>= 6 mm) in both groups. CAL was significantly greater in smokers throughout the study, but gains in attachment were similar for both groups (0.71 to 1.00 mm). BOP reductions were similar in both groups.Conclusions: Supragingival plaque control resulted in significant changes in clinical parameters associated with gingivitis and periodontitis. Smoking did not affect results, regardless of initial PD.

Robust state-derivative feedback LMI-based designs for multivariable linear systems

In some practical problems, for instance in the control systems for the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. New necessary and sufficient linear matrix inequalities (LMI) conditions for the design of state-derivative feedback for multi-input (MI) linear systems are proposed. For multi-input/multi-output (MIMO) linear time-invariant or time-varying plants, with or without uncertainties in their parameters, the proposed methods can include in the LMI-based control designs the specifications of the decay rate, bounds on the output peak, and bounds on the state-derivative feedback matrix K. These design procedures allow new specifications and also, they consider a broader class of plants than the related results available in the literature. The LMIs, when feasible, can be efficiently solved using convex programming techniques. Practical applications illustrate the efficiency of the proposed methods.

CONTROL OF UNCERTAIN DYNAMIC-SYSTEMS USING STRICTLY POSITIVE REAL SYSTEMS

This paper presents necessary and sufficient conditions to turn a linear time-invariant system with p outputs, m inputs, p greater-than-or-equal-to m and using only inputs and outputs measurements into a Strictly Positive Real (SPR).Two results are presented. In the first, the system compensation is made by two static compensators, one of which forward feeds the outputs and the second back feeds the outputs of the nominal system.The second result presents conditions for the Walcott and Zak variable structure observer-controller synthesis. In this problem, if the nominal system is given by {A,B,C}, then the compensated system is given by {A+GC,B,FC} where F and G are the constant compensation matrices. These results are useful in the control system with uncertainties.

On designing linear tunable high-Q OTA-C filters with low sensitivity

This paper discusses a design approach for a high-Q low-sensitivity OTA-C biquad bandpass section. An optimal relationship is established between transconductances defining the differencebeta - gamma in the Q-factor denominator, setting the Q-sensitivity to tuning voltages around unity. A 30-MHz filter was designed based on a 0.35 mum CMOS process and V-DD=3.3 V. A range of circuit simulation supports the theoretical analysis. Q-factor spans from 20.5 to 60, while ensuring filter stability along the tuning range. Although a triode-operating OTA is used, the procedure can be extended to other types of transconductor.

H-2 and H-infinity - norm control of intelligent structures using LMI techniques

Linear Matrix Inequalities (LMIs) is a powerful too] that has been used in many areas ranging from control engineering to system identification and structural design. There are many factors that make LMI appealing. One is the fact that a lot of design specifications and constrains can be formulated as LMIs [1]. Once formulated in terms of LMIs a problem can be solved efficiently by convex optimization algorithms. The basic idea of the LMI method is to formulate a given problem as an optimization problem with linear objective function and linear matrix inequalities constrains. An intelligent structure involves distributed sensors and actuators and a control law to apply localized actions, in order to minimize or reduce the response at selected conditions. The objective of this work is to implement techniques of control based on LMIs applied to smart structures.

Damage Characterization Using Guided-Wave Linear Arrays and Image Compounding Techniques

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A class of multiobjective control problems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bayesian L-optimal exact design of experiments for biological kinetic models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Inverter-fed linear asynchronous machine

The behaviors of an arc-shaped stator induction machine (the sector-motor) and a disc-secondary linear induction motor are analyzed in this work for different values of the frequency. Variable frequency is produced by a voltage source controlled-current inverter which keeps constant the r.m.s. value of the phase current, also assuring a sinusoidal waveform. For the simulations of the machine developed thrust, an equivalent circuit is used. It is obtained through the application of the one-dimensional theory to the modeling. The circuit parameters take into account the end effects, always present is these kind of machines. The phase current waveforms are analyzed for their harmonic contents. Experimental measurements were carried out in laboratory and are presented with the simulations, for comparison.

Global optimization approach for the H2-norm model reduction problem

A branch and bound algorithm is proposed to solve the H2-norm model reduction problem for continuous-time linear systems, with conditions assuring convergence to the global optimum in finite time. The lower and upper bounds used in the optimization procedure are obtained through Linear Matrix Inequalities formulations. Examples illustrate the results.

Control automatico de un sistema electrico mediante logica difusa

Substitution of fuzzy logic control in an electrical system normally controlled by proportional-integral frequency was studied and analyzed. A linear model of an electrical system, the concepts which govern the theory of fuzzy logic, and the application of this theory to systems control, are briefly presented. The methodology of fuzzy logic was then applied to develop a model for an electrical energy system. The results of the simulation demonstrated that fuzzy logic control eliminated the area frequency error and permitted that only the area experiencing an increase in charge responds to this variation. Based on the results, it is concluded that control based on fuzzy logic is simple, is easy to maintain, is of low cost, and can be used to substitute traditional velocity controllers.