Browsing by Author "Gallegos, Javier A."

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    Error-Based Switched Fractional Order Model Reference Adaptive Control for MIMO Linear Time Invariant Systems
    (2024) Aguila-Camacho, Norelys; Gallegos, Javier A.
    This paper presents the design and analysis of Switched Fractional Order Model Reference Adaptive Controllers (SFOMRAC) for Multiple Input Multiple Output (MIMO) linear systems with unknown parameters. The proposed controller uses adaptive laws whose derivation order switches between a fractional order and the integer order, according to a certain level of control error. The switching aims to use fractional orders when the control error is larger to improve transient response and system performance during large disturbed states, and to obtain smoother control signals, leading to a better control energy usage. Then, it switches to the integer order when the control error is smaller to improve steady state. Boundedness of all the signals in the scheme is analytically proved, as well as convergence of the control error to zero. Moreover, these properties are extended to the case when system states are affected by a bounded non-parametric disturbance. Simulation studies are carried out using different representative plants to be controlled, showing that fractional orders and switching error levels can be found in most of the cases, such as when SFOMRAC achieves a better balance among control energy and system performance than the non-switched equivalent strategies.
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    Robust Adaptive Average Consensus Over a Time-Varying and Nonbalanced Environment
    (2024) Gallegos, Javier A.; Schlotterbeck, Constanza; Nunez, Felipe
    Average consensus is a fundamental problem in distributed control that still lacks a general solution when the agents face nonideal conditions and uncertain environments. This note contributes to the topic by addressing average consensus in networks of agents that: 1) interact over a time-varying and nonbalanced environment and 2) face parametric and nonparametric disturbances. It is shown that an adaptive strategy, which combines surplus variables and virtual agents, effectively solves the exact average consensus problem in this nonideal and uncertain setup. A numerical example is presented to illustrate the potential of the proposed approach.