SUMMARYIn this paper, some experimental results and a performance analysis of a general control methodology for swinging up and stabilizing underactuated two-link robots are presented. The analyzed methodology is based on Euler-Lagrange dynamics, passivity analysis, and dynamic programming theory. The applied control method preserves the general structure of a suboptimal control approach, while the functional defining a performance index is based on the underactuated system energy. In order to illustrate the presented approach, the swing up and stabilization control of two experimental electromechanical underactuated systems about an unstable equilibrium point are shown.
When a diverse group of experts share their knowledge to ascertain and solve a particular multiple criteria decision-making (MCDM) problem, uncertainty arises from several sources. In those cases, the interval multiplicative preference relation (IMPR) approach is a useful technique when verifying consistency. As illustrated in this paper, the validation and the improvement of consistency require robust analysis tools and algorithms. The proposed methodology provides reliable and consistent IMPR, which can be quantified in terms of row geometric mean method (RGMM) or the eigenvalue method (EM). In this manner, decision makers’ choices are implicitly including their uncertainty while maintaining acceptable consistency. The present approach is based on the Hadamard’s dissimilarity operator and through an algorithm, the derivation of a reliable and consistent IMPR is synthesized. In order to illustrate our results and compare them appropriately with other methodologies, a few examples are addressed and solved.
In commercial organizations operations, frequently some dynamic events occur which involve operational, managerial, and valuable information aspects. Then, in order to make a sound decision, the business professional could be supported by a Multi Criteria Decision-Making (MCDM) system for taking an external course of action, as, for instance, forecasting a new market or product, up to an inner decision concerning for instance, the volume of manufacture. Thus, managers need, in a collective manner, to analyze the actual problems, to evaluate various options according to diverse criteria, and finally choose the best solution from a set of various alternatives. Throughout these processes, uncertainty and hesitancy easily arise, when it comes to define and judge criteria or alternatives. Several approaches have been introduced to allow Decision Makers (DMs) to deal with. The Interval Multiplicative Preference Relations (IMPRs) approach is a useful technique and the basis of our proposed methodology to provide reliable consistent and in consensus IMPRs. In this manner, DMs’ choices are implicitly including their uncertainty while maintaining both an acceptable individual consistency, as well as group consensus levels. The present method is based on some recent results and an optimization algorithm to derive reliable consistent and in consensus IMPRs. In order to illustrate our results and compare them with other methodologies, a few examples are addressed and solved.
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