Dr. Jairo Olguin Roque

Fixed-Time Sliding Mode Control of a Thrust-Vectored Planar VTOL UAV With Strongly Coupled Dynamics

Salaza Sergio

Iván González-Hernández

Rogelio Lozano

This paper proposes a robust algorithm based on a fixed-time sliding mode controller (FTSMC) for a Quadrotor aircraft. This approach is based on Lyapunov theory, which guarantees system stability. Nonlinear error dynamics techniques are used to achieve accurate trajectory tracking in the presence of disturbances. The performance of the FTSMC is compared with the typical non-singular terminal sliding mode controller (NTSMC) to evaluate its effectiveness. The numerical results show that FTSMC is more efficient than the typical NTSMC in disturbance reduction.

4 May 2026 in IEEE Access

Journal Article

Diego-Alfredo Padilla-Pérez

Pablo-Alejandro Arizpe-Carreón

Advanced Robust Control for a PVTOL System with High Input Coupling

This paper presents the design and numerical validation of a robust fixed-time sliding mode controller (FTSMC) for a thrust-vectored planar vertical takeoff and landing (PVTOL) system with strongly coupled nonlinear dynamics. Unlike conventional PVTOL models assuming aligned thrust, the proposed system explicitly incorporates thrust vectoring, resulting in significant inter-axis coupling. A fixed-time sliding-mode control law with smooth nonlinear terms is developed to ensure practical fixed-time convergence to a predefined boundary layer, independently of initial conditions, while mitigating chattering. Numerical simulations under bounded disturbances demonstrate that the proposed FTSMC outperforms a non-terminal sliding mode controller (NTSMC), achieving a reduction of approximately 38% in settling time, more than 80% reduction in pitch overshoot, and up to 60% decrease in control effort. These results highlight the robustness and efficiency of the proposed control strategy for safety-critical UAV and rocket-based platforms that require rapid, precise maneuvering.

31 October 2025

Book Chapter

Jhonatan-Fernando Eulopa-Hernandez

Adaptive Predefined-Time Neural Tracking Control with Switching Event-Triggered Mechanism for 6-DOF Quadrotor UAV: A Comparative Study against Backstepping Adaptive MTN

Pablo Alejandro Arizpe

Diego Padilla-Pérez

1 September 2026

Conference Paper

Improved Depth Imaging of the Chicxulub Impact Crater by GPU-Accelerated Adjoint Reverse Time Migration

Levi Emmanuel Cruz-Vázquez

Alondra Ruiz-Vidal

15 April 2026 in Symmetry

Journal Article

Jesús Antonio Herrera-Pérez

Carlos Ortiz Aleman

Sebastian López-Juárez

Backstepping Adaptive Multi-dimensional Taylor Network Control for Planar Vertical Take-Off and Landing Quadrotors: Cascade Design with Software-in-the-Loop Validation

Diego Padilla-Pérez

Reverse time migration (RTM) exploits time-reversal symmetry and adjoint duality to focus wavefields and reconstruct subsurface reflectivity, but large surveys remain limited by the cost of forward and backward propagation. We present a Graphics Processing Unit (GPU)-accelerated adjoint RTM workflow for depth imaging of the Chicxulub impact structure using the marine A0/A1 composite profile (1996). The processed stacked section contains 14,172 traces with 6.25 m Common Depth Point (CDP) spacing, 1 ms sampling, and 18 s record length. Forward and adjoint wavefields are computed with a staggered-grid finite-difference scheme (fourth order in space, second in time) and Convolutional Perfectly Matched Layers (CPMLs), which provide stable finite-domain simulations while introducing controlled symmetry breaking through absorption. The solver is verified with the Lamb half-space analytical benchmark and applied through five interpretation-guided velocity/density updates. The final depth image improves reflector continuity and interpretability of crater-scale elements, including post-impact sedimentary fill, melt and breccia units, terrace fault blocks, and deep uplift-related structure. Compute Unified Device Architecture (CUDA) acceleration reduces runtime from ∼32.36 h on a CPU baseline to ∼34.10 min on an RTX 3070 (≈56.9×), enabling practical, reproducible iterative RTM on accessible hardware.

27 October 2026

Book Chapter