In this paper we study the uniqueness of extremals satisfying first order necessary conditions for optimal control problems involving endpoint and control constraints. In particular we show that, for such problems, a strict Mangasarian-Fromovitz type constraint qualification does imply uniqueness of Lagrange multipliers but, contrary to the corresponding equivalence in mathematical programming, the converse in optimal control may not hold.
This article, present a new contribution to the control of wind energy systems, a robust nonlinear control of active and reactive power with the use of the Backstepping and Sliding Mode Control approach based on a doubly fed Induction Generator power (DFIG-Generator) in order to reduce the response time of the wind system. In the first step, a control strategy of the MPPT for the extraction of the maximum power of the turbine generator is presented. Subsequently, the Backstepping control technique followed by the sliding mode applied to the wind systems will be presented. These two types of control system rely on the stability of the system using the LYAPUNOV technique. Simulation results show performance in terms of set point tracking, stability and robustness versus wind speed variation.
Lexical meaning of the word “fuel” is a material that can be made to react with other substances in order to release chemical or nuclear energy as heat or to be used for work. Down the ages, energy has been one of the most important part of the human life. From past to present, heating and cooking are used intensively and during the history, fuel has been used both for cooking and heating. This paper introduces an integrated multiple criteria decision making approach for fuel provider selection in food industry. Seven conflicting evaluation criteria namely lead time, reliability, sustainability, cost, service quality, location and warranties, are determined in this work. In order to illustrate the application, a numerical example is given by conducting a case study in Turkish food sector.
We provide the scheme for driving a network modelled by dynamical system from one state ("undesired") to another one. This can be done by changing in time adjustable parameters and require knowledge of the structure of attractors of a system. The process is explained and illustrated by analyzing the two-element network.
The present study develops a decision support methodology for investment projects selection problem. The proposed methodology applies the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) approach under hesitant fuzzy environment. Selection of investment projects is made considering a set of weighted attributes. To evaluate attributes our approach implies using of experts' assessments. In the proposed methodology the values of the attributes are given by group of experts in the form of lingual assessments - linguistic terms. Then, these lingual assessments are expressed in trapezoidal fuzzy numbers. Consequently, proposed approach is based on hesitant trapezoidal fuzzy TOPSIS decision-making model. The case when the information on the attributes weights is completely unknown is considered. The attributes weights identification based on De Luca-Termini information entropy is offered in context of hesitant fuzzy sets. Following the TOPSIS algorithm, first the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are defined. Then the ranking of alternatives is performed in accordance with the proximity of their distances to the both FPIS and FNIS. An example is shown to explain the procedure of the proposed methodology.
