Kevin Puentes

Papers

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About

Kevin Puentes is a rising researcher in the field of intelligent control systems, with a focused expertise in the integration of neural networks and classical control theory for mobile robotics. His most cited work, "Enhancing Control Systems with Neural Network-Based Intelligent Controllers" (2024, 35 citations), tackles the fundamental challenge of managing the complex, nonlinear dynamics of mobile robots operating in unpredictable environments. By proposing neural controllers that adapt to system complexity, Puentes offers a robust solution for improving autonomous navigation. In his related study, "Trajectory Tracking of a Mobile Robot Using a PID Controller Combined with Neural Networks" (2023), he advances a cascade control strategy that synergizes a model-based kinematic controller for position error reduction with a neural network-enhanced inner loop for dynamic response. This dual-loop approach demonstrates his ability to bridge theoretical modeling with practical implementation. Though early in his career, Puentes’s work is already gaining traction, signaling his potential to shape the future of intelligent, adaptive robotics. His research is particularly valuable for students and engineers seeking to understand how neural networks can elevate traditional control architectures in real-world applications.