A Novel Hybrid (PID + MRAC) Adaptive Controller for an Air Levitation System

Bomfim, Marcelo Henrique Souza; Lima, Eduardo José; Monteiro, Nonato Mendonça Lott; Dias, André Lage A.

doi:10.1109/tla.2021.9475871

Cited by 6 publications

(3 citation statements)

References 21 publications

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“…This is because Simulink automatically adds interaction forces between the individual blocks of the model. In the SimInTech model, these interactions are absent, but they can be taken into account by complicating the original mathematical model [51,[66][67][68][69][70].…”

Section: Spider Robot Physics Modelmentioning

confidence: 99%

Mathematical Model of a Robot-spider for Group Control Synthesis: Derivation and Validation

Kravchenko,

Efremov,

Zhilenkov

et al. 2023

Journal of Robotics and Control

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A six-legged spider robot is a complex object from the point of view of the problem of synthesizing a system for controlling its movement. To synthesize an advanced control system for such a robot, which must solve non-trivial problems of overcoming obstacles, functioning under conditions of external disturbances, etc., we first solve the problem of synthesizing an information model of the object, on the basis of which its control system will subsequently be built.The paper compares two methods for synthesizing the information model of a six-legged spider-robot. In the first method, an information model is automatically synthesized from a CAD model of a spider-robot in a MATLAB-based graphical programming environment Simulink. In the second method, the information model is synthesized in the environment of dynamic modeling of technical systems SimInTech on the basis of a system of differential equations in the Cauchy form. Control loops and external influences are added to the information models synthesized in each of the modeling environments. The study showed that each of the resulting models has both its own individual advantages and disadvantages. They are mainly related to taking into account the mutual influence of various blocks of models on each other. It is shown that, in the end, the two models complement each other and make it possible to obtain an advanced basis for further synthesis of the motion control system.The results obtained in this work make it possible to use information models as a basis for the development of a control system for a physical model of a six-legged spider-robot, printed on a 3D printer and assembled on the basis of the Arduino hardware platform.

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Section: Spider Robot Physics Modelmentioning

confidence: 99%

Mathematical Model of a Robot-spider for Group Control Synthesis: Derivation and Validation

Kravchenko,

Efremov,

Zhilenkov

et al. 2023

Journal of Robotics and Control

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“…The MRAC is seen as the outer loop control, and the LADRC can be seen as the inner loop control. The 'total disturbance' in VSI system can be observed and compensated by ESO, thus the error between ESO output and reference model output can be reduced and make the system less sensitive [31]. And combined with the features of Narendra adaptive control, the parameters of the controller can be adjusted adaptively.…”

Section: Introductionmentioning

confidence: 99%

A Novel Narendra‐based adaptive anti‐disturbance control strategy for the microgrid inverters: A novel MG VSI adaptive anti‐disturbance control strategy based on Narendra theory

Shi

Chang

et al. 2023

IET Power Electronics

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The control performance of the voltage source inverter will be reduced when it operates under complex microgrid (MG) conditions. Traditionally, problems such as high controller order and complex design may occur when robust control and secondary regulation are adopted for the inverters. Meanwhile, when the conventional adaptive control is adopted, the adaptive gain may be too high, resulting in increased sensitivity of the system to external disturbances. To address the above problems, a novel Narendra‐based adaptive anti‐disturbance control strategy for microgrid voltage source inverter is proposed in this paper. Firstly, a Narendra adaptive‐based controller is constructed, which enables the controller to adaptively adjust the system parameters to change the inverter output voltage quality. Secondly, the extended state observer (ESO) is introduced to observe and suppress the total disturbance of the system, which can make the system less sensitive and ensure the stability of the system operation. Thirdly, according to the Lyapunov stability theory, the Lyapunov function is chosen to prove the global asymptotic stability of the system, and an adaptive law is designed. Finally, the comparative experiment shows that the proposed control strategy based on Narendra adaptive anti‐disturbance can maintain excellent voltage control performance in complex working conditions, and then ensure that the inverter's output voltage always meets power quality standard in complex working conditions.

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“…Another MRAC's advantage is that the expected performance can be defined through the reference model, in which the performance in terms of maximum overshooting and settling time can be defined. Another important feature of MRAC is that the stability analysis is embedded in the controller design, which removes the need for a posteriori stability analysis [31,32].…”

Section: Introductionmentioning

confidence: 99%

Modelling, simulation and implementation of a hybrid model reference adaptive controller applied to a manipulator driven by pneumatic artificial muscles

2021

Self Cite

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The present research aims to model, simulate and implement a new hybrid control approach based on a combination of proportional integral derivative (PID) Controller and Model Reference Adaptive Controller (MRAC), in which Lyapunov’s theory is used to ensure asymptotic stability to control a two degrees of freedom (DoF) manipulator driven by McKibben’s artificial pneumatic muscles. The MRAC controller works as a nonlinearity compensator and PID controller works during the transient period, as the MRAC performs poorly in this regime. This new approach is entitled Hybrid Model Reference Adaptive Controller (H-MRAC) and it has an unprecedented topological structure based on three terms. The feedforward term acts in disturbances rejection, the derivative term in oscillations damping and the feedback term acts in error convergence to zero. In this article, a control system dedicated to pneumatic manipulators was developed. As a result, proof of asymptotic convergence was performed for the proposed topological approach, which was validated on a two DoF manipulator. The proposed mechanism satisfactorily met the ISO/TS 15066 standard, and the position tracking obtained a global error of 37.69% and 51.01% smaller than found in the literature examples, entitled MRAC and A-PID, respectively, for simulations and 37.46% and 30.25% for experiments.

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A Novel Hybrid (PID + MRAC) Adaptive Controller for an Air Levitation System

Cited by 6 publications

References 21 publications

Mathematical Model of a Robot-spider for Group Control Synthesis: Derivation and Validation

Mathematical Model of a Robot-spider for Group Control Synthesis: Derivation and Validation

A Novel Narendra‐based adaptive anti‐disturbance control strategy for the microgrid inverters: A novel MG VSI adaptive anti‐disturbance control strategy based on Narendra theory

Modelling, simulation and implementation of a hybrid model reference adaptive controller applied to a manipulator driven by pneumatic artificial muscles

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