A comparison between optimal LQR control and LQR predictive control of a planar robot of 2DOF

OrteganVidal, A.; SalazarnVasquez, F.; RojasnMoreno, Arturo

doi:10.1109/intercon50315.2020.9220263

Cited by 11 publications

(5 citation statements)

References 3 publications

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“…However, even though MPC allows optimization of system performance based on the desired criteria, the computational power of this method remains a significant downside that limits its proliferation. Creating a complex mathematical model, as well as computing the optimal solution at each time step, is a challenging task for most mechanisms and productions [21,108].…”

Section: Other Modern Methodsmentioning

confidence: 99%

Principles and Methods of Servomotor Control: Comparative Analysis and Applications

Autsou,

Kudelina,

Vaimann

et al. 2024

Applied Sciences

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Servomotors have found widespread application in many areas, such as manufacturing, robotics, automation, and others. Thus, the control of servomotors is divided into various principles and methods, leading to a high diversity of control systems. This article provides an overview of types of servomotors and their basic principles and control methods. Principles such as digital signal processing, feedback control principle, field-oriented control, and integration with Industry 4.0 are discussed. Based on these control principles, the article presents popular control methods: PWM control, current control, two-loop control, fuzzy-logic control, and programmable control. The article concludes with a comparison of the presented methods on several criteria, and as an example, it includes the results of modeling a servomotor using the fuzzy-logic control method.

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Section: Other Modern Methodsmentioning

confidence: 99%

Principles and Methods of Servomotor Control: Comparative Analysis and Applications

Autsou,

Kudelina,

Vaimann

et al. 2024

Applied Sciences

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“…The study looked at a "X-configuration quadcopter" and the saturation function, but the main flaw was that it ignored external disturbances. There are several LQR controllers designed for quadcopters in the literature [5][6][7]. Dhewa et al [8] designed and implemented a quadrotor control system based on the LQR method to find the best value for the feedback gain K in the hover condition.…”

Section: Original Research Articlementioning

confidence: 99%

“…is the inertia of the rotor, and , , and are the inertia of the quadrotor in and respectively. (7) (8) (9) (10) (11) Where b is the thrust coefficient and d is the drag coefficient. The angular speed for each rotor is .…”

Section: Quadcopter Working Principle and Dynamic Modelmentioning

confidence: 99%

Implementation and Stabilization of a Quadcopter Using Arduino and the Combination of LQR and SMC Methods

Elagib

Karaasrlan²

2022

JERR

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This paper presents a combination of Linear Quadratic Regulator (LQR) and Sliding Mode Control (SMC) methods to control a four-rotor unmanned aerial vehicle (UAV) that takes off and lands vertically (VTOL). Although controlling UAVs is difficult due to their highly nonlinear characteristics, the controller successfully controlled and stabilized the quadcopter in altitude and attitude by combining the advantages of the nonlinear and linear controllers. The Newton-Euler method is employed to build the dynamic model of the quadcopter, which is divided into two subsystems: the under-controlled subsystem and the fully actuated subsystem. The entire controller model was demonstrated in MATLAB/Simulink, and results demonstrating the controller's performance in various scenarios were obtained.

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“…Various papers have studied helical motion resolvers [5]- [6]. However, 2-DOF planar electrical machines, which are used in x-y Tables, pantograph type planar robots [7], scanning probe microscopes, and optical fiber alignments [8], need the mover position measured in two perpendicular directions of linear motion. Different types of linear position sensors are proposed in the literature [9]- [12], and the concept design for the 2-DOF linear resolver is presented in [12] for the first time.…”

Section: Introductionmentioning

confidence: 99%

Magnetic Equivalent Circuit Model for Performance Prediction of Two-DOF Planar Resolver

Zare,

Tootoonchian,

Daniar

et al. 2023

IEEE Access

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In this paper, an analytical model based on the Magnetic Equivalent Circuit (MEC) method is developed for a planar wound mover two-degree of freedom (2-DOF) resolver. Planar resolvers enable mass, volume, and complexity reductions for position control of 2-DOF linear actuators. However, similar to any other linear electromagnetic sensors, the performance of the planar resolvers is negatively affected by the limited dimensions of the mover's ferromagnetic core. Thus, it is necessary to develop an appropriate compensation method. On the other hand, the 3-D geometry of the sensor necessitates extremely time consuming 3-D time-stepping analysis. Therefore, a fast yet accurate analytical model is critical for the iterative design and compensation algorithm. In order to address these modeling limitations, the slot-tooth region and longitudinal end effect are included in the model. Then, its accuracy is verified by comparing the results with those of the 3-D time stepping finite element method (TSFEM). Then, the developed model is employed for design optimization to compensate for the end effects. Finally, the optimal sensor is experimentally prototyped and tested.

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A comparison between optimal LQR control and LQR predictive control of a planar robot of 2DOF

Cited by 11 publications

References 3 publications

Principles and Methods of Servomotor Control: Comparative Analysis and Applications

Principles and Methods of Servomotor Control: Comparative Analysis and Applications

Implementation and Stabilization of a Quadcopter Using Arduino and the Combination of LQR and SMC Methods

Magnetic Equivalent Circuit Model for Performance Prediction of Two-DOF Planar Resolver

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