{"product_id":"analysis-of-the-hierarchical-fuzzy-control-using-evolutionary-algorithms-365916884x","title":"Analysis of the hierarchical fuzzy control: using evolutionary algorithms","description":"\u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 365916884X\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Zajaczkowski, Juliusz\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e New\u003c\/p\u003e\u003cp\u003eThe research presented examines the construction of a fuzzy logic controller for complex nonlinear system by control system decomposition into hierarchical fuzzy logic sub-systems. Evolutionary algorithm based methods are proposed to determine the control system for the hierarchical fuzzy system (HFS). Different HFS topologies for a given dynamical system (such as the inverted pendulum system) are investigated. For the inverted pendulum system, a single layer, two layered, three layered, and four layered HFS, with different variable input configuration is investigated. Effects of different input configurations on controller performance are examined and discussed. A new evolutionary algorithm based compositional method is proposed to control system over the whole set of user-defined initial conditions. The method addresses directly the problem of controlling the dynamical system from specific, user-defined initial conditions. The multiobjective evolutionary algorithm (MOEA) based compositional method is developed and tested on the example of the inverted pendulum system.\u003c\/p\u003e","brand":"Mia Karts","offers":[{"title":"Default Title","offer_id":68223692407072,"sku":"NEW365916884X","price":110.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/51a7kmRzL_L.jpg?v=1794319118","url":"https:\/\/miakarts.com\/products\/analysis-of-the-hierarchical-fuzzy-control-using-evolutionary-algorithms-365916884x","provider":"Miakarts Books","version":"1.0","type":"link"}