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Michele Pagone

Publications and source records attributed to Michele Pagone.

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A Finite-Gain Stability Approach to NMPC Design: the Extended Version

This paper proposes a novel approach to design of Nonlinear Model Predictive Control (NMPC) schemes based on Finite-Gain Stability (FGS) concepts. The proposed formulation considers the case where the plant is affected by unknown but bounded disturbances, which renders difficult the classical Lyapunov-based analysis/design. Based on FGS conditions for a closed-loop system, we develop a systematic NMPC design methodology, allowing us to choose the relevant NMPC parameters that lead to closed-loop FGS and provide a satisfactory tracking performance, also for the case of time-varying reference signals. A simulated example is presented to demonstrate the effectiveness of our framework, concerned with lateral/longitudinal control of an automated vehicle.

eess.SY

Noise Models in the LISA Mission

This document briefly describes the noise models and shapes used for the synthesis of the Drag-Free and Attitude Control System in the LISA space mission. LISA (Laser Interferometer Space Antenna) is one of the next large-class missions from the European Space Agency (ESA), expected to be launched in 2034. The main goal of the mission is to detect the gravitational waves, which are undulatory perturbations of the space-time fabric, extremely important to collect experimental proofs for the General Relativity Theory. In the 90s, different international collaborations of institutes laid the foundations for the first ground-based interferometers (see, e.g., LIGO and Virgo). However, ground-based interferometers have a limited bandwidth due to the Earth's environmental noises and short arm-length of few kilometers. Therefore, they cannot observe gravitational waves belonging to the portion of the spectrum below 1 Hz. This issue can be overcome by means of space-based interferometers, that can have arm-lengths up to millions of kilometers and exploit a quieter environment than the Earth's surface. The LISA system is affected by actuation, sensing and environmental disturbances and noises. Among the actuation noises we have those given by the Micro Propulsion System (MPS), the Gravitational Reference Sensor (GRS) and the Optical Assembly (OA) motor. Among the sensing noises we consider the interferometer, the Differential Wavefront Sensor (DWS) and the GRS. The environmental disturbances are given by the solar radiation pressure, the test-mass stiffness and self-gravity, and the environmental noises acting directly on the test-mass.

astro-ph.IM

A Minimum-propellant Pontryagin-based Nonlinear MPC for Spacecraft Rendezvous in Lunar Orbit: the Extended Version

We propose a Nonlinear Model Predictive Control approach to spacecraft rendezvous in non-Keplerian Lunar orbits. The approach is based on the Pontryagin Minimum Principle and allows the accomplishment of minimum-propellant maneuvers. The relative motion between the chaser and the target is described by the nonlinear and unstable dynamics of the circular restricted three body-problem. In the proposed formulation, we design a minimum-propellant controller, which leads to a bang-bang behavior of the control signal. Under suitable assumptions, simplified dynamics is employed as prediction model, in order to reduce the complexity of the controller algorithm but, at the same time, without penalizing the controller tracking performance. The proposed approach's effectiveness is validated by a simulation example.

eess.SY

A barrier function approach to constrained Pontryagin-based Nonlinear Model Predictive Control

A Pontryagin-based approach to solve a class of constrained Nonlinear Model Predictive Control problems is proposed which employs the method of barrier functions for dealing with the state constraints. Unlike the existing works in literature the proposed method is able to cope with nonlinear input and state constraints without any significant modification of the optimization algorithm. A stability analysis of the closed-loop system is carried out by using the L-2 norm of the predicted state tracking error as a Lyapunov function. Theoretical results are tested and confirmed by numerical simulations on the Lotka-Volterra prey/predator system.

math.OC