On the Rejection of Random Perturbations and the Tracking of Random References in a Quadrotor

Meda-Campaña, J. A.; Escobedo-Alva, Jonathan Omega; Rubio, José de Jesús; Aguilar-Ibáñez, Carlos; Pérez-Cruz, J. Humberto; Obregon-Pulido, G.; Tapia-Herrera, Ricardo; Orozco, Eduardo; Cordova, Daniel Andres; Islas, Marco Antonio

doi:10.1155/2022/3981340

Cited by 8 publications

(5 citation statements)

References 30 publications

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“…Notice that in [13], both techniques have already been blended into a control scheme to achieve the tracking/rejecting of random signals. However, the main drawback of such an approach is that the explicit mathematical model of the exosystem is required to apply the regulation presented there.…”

Section: B Regulation Theorymentioning

confidence: 99%

The Output Regulation and the Kalman Filter as the Signal Generator

Meda-Campaña,

Torres-Cruz,

Rojas-Ruiz

et al. 2023

IEEE Access

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In this work, the problem of following references and rejecting disturbances that are contaminated with noise and whose dynamics are too complex to have a mathematical model that describes the behavior of such signals is studied. In addition to exploiting the capabilities of the Kalman filter (KF) to clean the signals so that they can serve as external signals for the regulation theory, the construction of the generating system (exosystem) is proposed as a diagonal system by blocks, where each block is a Kalman filter that estimates each one of the corresponding reference/disturbance signals. The viability of the approach is verified by two examples, mimicking the problem of tracking a flying object moving freely in the 3D space by a quadrotor which is under the influence of the proposed controller when the displacements of the arbitrary flying object are measured by low-cost sensors.

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Section: B Regulation Theorymentioning

confidence: 99%

The Output Regulation and the Kalman Filter as the Signal Generator

Meda-Campaña,

Torres-Cruz,

Rojas-Ruiz

et al. 2023

IEEE Access

Self Cite

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“…At the same time tracking control with time-varying external disturbances has been addressed by feedback linearization for a three-rotor UAV and proof stability via Lyapunov analysis [5]. The extension of the output regulation to random references/disturbances in a quadrotor for a hybrid exosystem [6] where the Kalman filter is used.…”

Section: Introductionmentioning

confidence: 99%

On the Output Regulation for an Underactuated Inverse Pendulum When the Exosystem Is a High-Gain Observer

et al. 2023

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This paper is devoted to solving the output regulation problem on the basis of the new Francis equations for arbitrary reference/disturbance signals, whose model are obtained by High-Gain observers, providing in this way, the regulation of unmodeled but measurable reference signals. The design is given by fixing a steady state globally attractive by means of LMIs which allows controlling the decay rate by considering input bounds; while the regulation problem is solved by computing the steady-state input based on a modified set of the regulation equations, when the exosystem is constructed upon High-Gain observers, extending in this way, the classical output regulation theory for unmodeled reference/disturbance signal. The Furuta pendulum is used to illustrate the viability of the proposed approach.INDEX TERMS Output regulation, high-gain observer, linear matrix inequality.

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“…Designing a robust controller for uncertain systems that can accommodate such uncertainties has always been an important yet challenging problem. To retain the robustness property, various robust control methods have been developed against model uncertainties [3][4][5][6][7][8]. Conventional robust control methods, however, were studied mainly via offline means.…”

Section: Introductionmentioning

confidence: 99%

Robust Trajectory Tracking of Uncertain Systems via Adaptive Critic Learning

2022

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This study develops an adaptive dynamic programming (ADP) scheme for uncertain systems to achieve the robust trajectory tracking. In this framework, the augmented state is first established via combining the tracking error and reference trajectory, where the robust tracking control problem can be resolved using the regulation control strategy. Then, the robust control problem of uncertain system can be represented as an optimal control problem of nominal system, which provides a new pathway to address the robust control problem. To realize the optimal control, the derived Hamilton–Jacobi–Bellman equation (HJBE) is solved by training a critic neural network (CNN). Finally, two innovative critic learning techniques are suggested to calculate the unknown NN weights, where the convergence of NN weights can be guaranteed. Simulations are carried out to demonstrate the effectiveness of the proposed method.

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On the Rejection of Random Perturbations and the Tracking of Random References in a Quadrotor

Cited by 8 publications

References 30 publications

The Output Regulation and the Kalman Filter as the Signal Generator

The Output Regulation and the Kalman Filter as the Signal Generator

On the Output Regulation for an Underactuated Inverse Pendulum When the Exosystem Is a High-Gain Observer

Robust Trajectory Tracking of Uncertain Systems via Adaptive Critic Learning

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