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Ricardo A. Ramirez-Mendoza

Researcher at Monterrey Institute of Technology and Higher Education

Publications -  234
Citations -  2069

Ricardo A. Ramirez-Mendoza is an academic researcher from Monterrey Institute of Technology and Higher Education. The author has contributed to research in topics: Damper & Computer science. The author has an hindex of 15, co-authored 195 publications receiving 1139 citations. Previous affiliations of Ricardo A. Ramirez-Mendoza include University of Monterrey.

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Influence of MR damper modeling on vehicle dynamics

TL;DR: In this paper, the influence of magneto-rheological damper modeling in vehicle dynamics analysis is studied and several tests using CarSim??compare a four-corner controlled semi-active suspension for two different magneto-, rheological, damper models.

Road Adaptive Semi-active Suspension in a Pick-up Truck using an LPV Controller

TL;DR: In this article, a road profile detector is proposed based on the frequency and amplitude estimation of the road irregularities by using a Fourier analysis and an H∞ robust observer is designed to estimate the variables related to the QoV vertical dynamics.
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Environment Classification Using Machine Learning Methods for Eco-Driving Strategies in Intelligent Vehicles

TL;DR: A method for machine-learning-based driving environment classification that does not involve computer vision but instead makes use of dynamics variables from Inertial-Measurement-Unit sensors and instantaneous energy consumption measurements is obtained.
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Direct Data-Driven Control for Cascade Control System

TL;DR: This paper combines system identification, direct data-driven control, and optimization algorithm to design two controllers for one cascade control system, that is, the inner controller and the outer controller.
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Disturbance Rejection in a One-Half Semiactive Vehicle Suspension by means of a Fuzzy-H ∞ Controller

TL;DR: A fuzzy-H∞ control, improved with weighting functions, has been designed and applied to a novel model of a one-half semiactive lateral vehicle (OHSLV) suspension and complies with all performance criteria compared with a benchmark passive average suspension that fails in satisfying most of the performance criteria.