Papers
6
Total Citations
81
H-Index
4
About
Isaac Gandarilla is a control systems researcher whose work centers on the stabilization and trajectory tracking of underactuated robotic systems, with a particular emphasis on self-balancing robots (SBRs) and robot manipulators. His major contributions lie in the application of advanced nonlinear control techniques, including interconnection and damping assignment passivity-based control (IDA-PBC), PID passivity-based control, and adaptive neural networks. In his most cited work (34 citations), Gandarilla developed an IDA-PBC strategy for a two-degree-of-freedom self-balancing robot, achieving robust stabilization through energy shaping. He further advanced the field by combining adaptive neural networks with input-output linearization to ensure precise trajectory tracking for SBRs, a scheme that rigorously addresses both external and internal dynamics (17 citations). More recently, he has extended his expertise to robot manipulators, proposing composite adaptive control methods that handle friction as an additive disturbance and integrating neural network compensation with PID control for improved tracking performance. Gandarilla’s research is distinguished by its systematic approach to underactuated systems, offering practical solutions that bridge theoretical control design with real-world robotic applications.
Research Focus
Key Achievements
Top Papers
- 1Control of a self-balancing robot with two degrees of freedom via IDA-PBC34 citations · 2018
- 2
- 3
- 4
- 5
- 6Stabilization of a self-balancing robot by energy shaping2 citations · 2018