7 papers · 1 filter
Data-Driven Adaptive Second-Order Sliding Mode Control with Noisy Data
Behrad Samari, Gian Paolo Incremona, Antonella Ferrara +1
This paper proposes a data-driven approach to designing adaptive suboptimal second-order sliding mode (ASSOSM) controllers for a class of single-input nonlinear systems with partia…
Robust data-driven model-reference control of linear perturbed systems via sliding mode generation
Giorgio Riva, Gian Paolo Incremona, Simone Formentin +1
This paper introduces a data-based integral sliding mode control scheme for robustification of model-reference controllers, accommodating generic multivariable linear systems with…
Distributed Koopman Operator Learning from Sequential Observations
Ali Azarbahram, Shenyu Liu, Gian Paolo Incremona
This paper presents a distributed Koopman operator learning framework for modeling unknown nonlinear dynamics using sequential observations from multiple agents. Each agent estimat…
Distributed Koopman Operator Learning for Perception and Safe Navigation
Ali Azarbahram, Shenyu Liu, Gian Paolo Incremona
This paper presents a unified and scalable framework for predictive and safe autonomous navigation in dynamic transportation environments by integrating model predictive control (M…
Distributed Switching Model Predictive Control Meets Koopman Operator for Dynamic Obstacle Avoidance
Ali Azarbahram, Chrystian Pool Yuca Huanca, Gian Paolo Incremona +1
This paper introduces a Koopman-enhanced distributed switched model predictive control (SMPC) framework for safe and scalable navigation of quadrotor unmanned aerial vehicles (UAVs…
From Data to Sliding Mode Control of Uncertain Large-Scale Networks with Unknown Dynamics
Behrad Samari, Gian Paolo Incremona, Antonella Ferrara +1
Large-scale interconnected networks, composed of multiple low-dimensional subsystems, serve as a crucial framework for modeling a wide range of real-world applications. Despite off…