Robust Controller Numerical Design for Reinforced Concrete Structures Under Seismic Excitation Conditions

Abstract

The article discusses driver optimization design issues that combine the evolution of artificial intelligence of the bat optimization algorithm with fuzzy drivers to enable practical applications in construction. The designation of system controllers includes various subsections such as initial system parameters, EB optimization algorithm, cloud controllers, stability analysis, and excitation sensors. The advantage of this design is the integrated H2 / H output of a robust strategy for certain systems with continuous and polyhedral uncertainties f or. The asymptote was obtained by adjusting the design parameters with the help of correction criteria. Numerical verification of the time and frequency domain shows the new system design to accurately predict and control the structural displacement reactions required to actively control each model structure . The Genetic Algorithm Test technique uses the Hurwitz Matrix Functional Structure hierarchy for hierarchical conditions and measures of exacerbation of effect. This article proposes any type of dynamic controller to obtain the optimal power structure required for active control of nonlinear structures. This method has shown favorable results in the resolutions of closed systems.

Keywords

• genetic design algorithm
• simulation method
• fuzzy logic reasoning
• the evolutionary algorithm of bats