Robust Active Disturbance Rejection Control via Control Lyapunov Functions: Application to Actuated-Ankle–Foot-Orthosis

Guerrero-Castellanos, J.F.; Rifaï, Hala; Arnez-Paniagua, V.; Linares-Flores, J.; Saynes-Torres, L.; Mohammed, Samer

doi:10.1016/j.conengprac.2018.08.008

Cited by 44 publications

(19 citation statements)

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“…En ese sentido el esquema de control por rechazo activo de perturbaciones ADRC (del sus siglas en inglés, Active Disturbance Rejection Control) introducido por (Han, 2009) se hace muy atractivo, ya que se basa en la capacidad de estimar en línea, vía un observador de estado extendido (ESO), la parte de la dinámica desconocida del sistema a controlar, así como todos los efectos externos adversos, para posteriormente cancelarlos mediante una apropiada ley de control, (Hebertt Sira-Ramírez and Zurita-Bustamante, 2017). La metodología ADRC, conjuntamente con la propiedad de planitud diferencial (ver la excelente explicación de (Sira-Ramírez et al, 2015)) ha sido utilizada ampliamente en variasáreas tales como el diseño de filtros de potencia reportando en (Fuentes et al, 2015), convertidores DC en (Sira-Ramírez et al, 2016), generación eléctrica a base de fuentes energías renovables, (Hernandez-Méndez et al, 2017), incluso robótica de asistencia, (Guerrero-Castellanos et al, 2018).…”

Section: Antecedentes Y Estado Del Arteunclassified

Comunicación distribuida activada por eventos para la sincronización de velocidad angular de motores BLDC en red

Hernández‐Méndez

Guerrero-Castellanos

Orozco-Urbieta

et al. 2021

Rev. iberoam. autom. inform. ind.

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Este trabajo presenta el diseño e implementación de un control colaborativo descentralizado para la sincronización de velocidad angular de un conjunto de motores de corriente continua sin escobillas (BLDC) distribuidos espacialmente. Apoyándose de un control por rechazo activo de perturbaciones, actuando como un bucle interno, la dinámica del BLDC puede asimilarse a la de un integrador de primer orden y el cual será considerado un agente. Se propone entonces una estrategia de control colaborativo descentralizado con una comunicación activada por eventos, que resuelve el problema del consenso líder-seguidor del sistema multi-agente y, con ello, la sincronización de velocidades entre motores. La topología de comunicación entre agentes se modela usando un grafo conectado y no dirigido. La ley de control descentralizado incorpora una función de evento, que indica el instante en el que $i$-ésimo agente transmite la información de velocidad angular a su vecino. El intercambio asíncrono de información permite reducir el tráfico de datos en la red de comunicaciones, lo que permite aprovechar el ancho de banda. Al analizar la dinámica de la trayectoria del error del sistema, se establece que el vector de error del sistema multi-agente tiende de forma exponencial y permanece confinado a una vecindad del origen del espacio de estados de error. Aunque la estrategia está diseñada para n-agentes, se desarrolló una plataforma experimental compuesta por dos motores y un líder virtual, permitiendo validar la estrategia. Los resultados experimentales muestran un excelente desempeño del consenso de velocidad angular de ambos motores BLDC para tareas de regulación, mientras que el uso del ancho de banda es de solamente 1.25 % con respecto a una implementación de comunicación periódica.

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Section: Antecedentes Y Estado Del Arteunclassified

Comunicación distribuida activada por eventos para la sincronización de velocidad angular de motores BLDC en red

Hernández‐Méndez

Guerrero-Castellanos

Orozco-Urbieta

et al. 2021

Rev. iberoam. autom. inform. ind.

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“…The motion control usually needs to follow an example, as shown in the work by Guerrero et al, where 20 healthy subjects participated to provide a gait example [80]. In the case of the absence of an example, it is necessary to predict the intended motion.…”

Section: Motion Path Controlmentioning

confidence: 99%

A Review on the Control of the Mechanical Properties of Ankle Foot Orthosis for Gait Assistance

et al. 2019

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In the past decade, advanced technologies in robotics have been explored to enhance the rehabilitation of post-stroke patients. Previous works have shown that gait assistance for post-stroke patients can be provided through the use of robotics technology in ancillary equipment, such as Ankle Foot Orthosis (AFO). An AFO is usually used to assist patients with spasticity or foot drop problems. There are several types of AFOs, depending on the flexibility of the joint, such as rigid, flexible rigid, and articulated AFOs. A rigid AFO has a fixed joint, and a flexible rigid AFO has a more flexible joint, while the articulated AFO has a freely rotating ankle joint, where the mechanical properties of the AFO are more controllable compared to the other two types of AFOs. This paper reviews the control of the mechanical properties of existing AFOs for gait assistance in post-stroke patients. Several aspects that affect the control of the mechanical properties of an AFO, such as the controller input, number of gait phases, controller output reference, and controller performance evaluation are discussed and compared. Thus, this paper will be of interest to AFO researchers or developers who would like to design their own AFOs with the most suitable mechanical properties based on their application. The controller input and the number of gait phases are discussed first. Then, the discussion moves forward to the methods of estimating the controller output reference, which is the main focus of this study. Based on the estimation method, the gait control strategies can be classified into subject-oriented estimations and phase-oriented estimations. Finally, suggestions for future studies are addressed, one of which is the application of the adaptive controller output reference to maximize the benefits of the AFO to users.

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“…Results are compared for PID and ADRC, for the hip and knee trajectories based on error comparison the results show a better performance of ADRC over PID. To keep track of active ankle-foot orthosis (AAFO) [ 40 ], a framework similar to [ 39 ] is used in which the authors modified the ADRC with the inclusion of Control Lyapunov Function (CLF) instead of PD controller, with Sontag’s formula. Stability is checked by input to state (ISS) framework where modification and experiments prove ARDC’s effectiveness.…”

Section: Introductionmentioning

confidence: 99%

Improved Active Disturbance Rejection Control for Trajectory Tracking Control of Lower Limb Robotic Rehabilitation Exoskeleton

Aole¹,

Elamvazuthi

Waghmare³

et al. 2020

Sensors

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Neurological disorders such as cerebral paralysis, spinal cord injuries, and strokes, result in the impairment of motor control and induce functional difficulties to human beings like walking, standing, etc. Physical injuries due to accidents and muscular weaknesses caused by aging affect people and can cause them to lose their ability to perform daily routine functions. In order to help people recover or improve their dysfunctional activities and quality of life after accidents or strokes, assistive devices like exoskeletons and orthoses are developed. Control strategies for control of exoskeletons are developed with the desired intention of improving the quality of treatment. Amongst recent control strategies used for rehabilitation robots, active disturbance rejection control (ADRC) strategy is a systematic way out from a robust control paradox with possibilities and promises. In this modern era, we always try to find the solution in order to have minimum resources and maximum output, and in robotics-control, to approach the same condition observer-based control strategies is an added advantage where it uses a state estimation method which reduces the requirement of sensors that is used for measuring every state. This paper introduces improved active disturbance rejection control (I-ADRC) controllers as a combination of linear extended state observer (LESO), tracking differentiator (TD), and nonlinear state error feedback (NLSEF). The proposed controllers were evaluated through simulation by investigating the sagittal plane gait trajectory tracking performance of two degrees of freedom, Lower Limb Robotic Rehabilitation Exoskeleton (LLRRE). This multiple input multiple output (MIMO) LLRRE has two joints, one at the hip and other at the knee. In the simulation study, the proposed controllers show reduced trajectory tracking error, elimination of random, constant, and harmonic disturbances, robustness against parameter variations, and under the influence of noise, with improvement in performance indices, indicates its enhanced tracking performance. These promising simulation results would be validated experimentally in the next phase of research.

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Robust Active Disturbance Rejection Control via Control Lyapunov Functions: Application to Actuated-Ankle–Foot-Orthosis

Cited by 44 publications

References 45 publications

Comunicación distribuida activada por eventos para la sincronización de velocidad angular de motores BLDC en red

Comunicación distribuida activada por eventos para la sincronización de velocidad angular de motores BLDC en red

A Review on the Control of the Mechanical Properties of Ankle Foot Orthosis for Gait Assistance

Improved Active Disturbance Rejection Control for Trajectory Tracking Control of Lower Limb Robotic Rehabilitation Exoskeleton

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