Dr. JORGE DANIEL RÍOS ARRAÑAGA
Resumen curricular:
El Dr. Jorge Daniel Ríos Arrañaga es profesor e investigador del Departamento de Innovación Basada en la Información y el Conocimiento en el Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI) de la Universidad de Guadalajara (UdeG). Actualmente se desempeña como Coordinador de la Maestría en Ciencias en Robótica e Inteligencia Artificial del mismo centro universitario. Miembro Nivel 1 del Sistema Nacional de Investigadoras e Investigadores (SNII) de México y miembro activo del IEEE, el Dr. Ríos desarrolla su labor académica y científica en las áreas de Sistemas Ciber-Físicos, Inteligencia Artificial, Sistemas Inteligentes, Control Automático y Robótica. Sus proyectos de investigación se llevan a cabo en el Laboratorio de Sistemas Ciber-Físicos, donde contribuye activamente al avance del conocimiento científico y a la formación de nuevas generaciones de especialistas, fomentando la vinculación entre investigación, docencia y la solución de problemas tecnológicos de vanguardia.
Perfil de Investigador SNII:
Perfil PRODEP:
Bases de datos bibliográficas:
Publicaciones del académico:
- PID Control of a PMDC Motor Identified with RHONN and EKF for Performance Improvement
- Edge-Weighted Consensus-Based Formation Control with Collision Avoidance for Mobile Robots Based on Multi-Strategy Mutation Differential Evolution
- Exponential sliding mode controller for tracking trajectory of nonlinear systems
- A Metaheuristic Optimization Approach to Solve Inverse Kinematics of Mobile Dual-Arm Robots
- Impulsive Pinning Control of Discrete-Time Complex Networks with Time-Varying Connections
- Formation Control of Mobile Robots Based on Pin Control of Complex Networks
- Real‐time neural observer‐based controller for unknown nonlinear discrete delayed systems
- Real‐time neural observer‐based controller for unknown nonlinear discrete delayed systems
- Real-time neural observer-based controller for unknown nonlinear discrete delayed systems
- Discrete-time neural control of quantized nonlinear systems with delays: Applied to a three-phase linear induction motor
- Environment classification for unmanned aerial vehicle using convolutional neural networks
- Real-time neural control of all-terrain tracked robots with unknown dynamics andnetwork communication delays
- Real-time neural control of all-terrain tracked robots with unknown dynamics and network communication delays
- Adaptive single neuron anti-windup PID controller based on the extended Kalman filter algorithm
- An autonomous path controller in a system on chip for shrimp robot
- Neural Evolutionary Predictive Control for Linear Induction Motors with Experimental Data
- Neural networks modeling and control: Applications for unknown nonlinear delayed systems in discrete time
- Studies in Computational Intelligence
- High-order sliding modes based on-line training algorithm for recurrent high-order neural networks
- Germinal Center Optimization Applied to Recurrent High Order Neural Network Observer
- Reduced-order Observer for State-dependent Coefficient Factorized Nonlinear Systems
- Advances in Intelligent Systems and Computing
- Germinal Center Optimization Applied to Neural Inverse Optimal Control for an All-Terrain Tracked Robot
- RHONN identifier-control scheme for nonlinear discrete-time systems with unknown time-delays
- Neural Identifier-Control Scheme for Nonlinear Discrete Systems with Input Delay
- Recurrent High Order Neural Observer for Discrete-Time Non-Linear Systems with Unknown Time-Delay
- Real-time neural identification and inverse optimal control for a tracked robot
- RHONN identifier for unknown nonlinear discrete-time delay systems
- Real-time discrete neural control applied to a Linear Induction Motor
- Neural identifier for unknown discrete-time nonlinear delayed systems