Analysis Accuracy in Positioning Calculation for Three-Degree-of-Freedom Spherical Actuator

Fusayasu, H.; Masuyama, Yuji; Hirata, Katsuhiro; Niguchi, Noboru; Takahara, Kenji

doi:10.1109/tmag.2021.3067323

Cited by 8 publications

(7 citation statements)

References 7 publications

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“…12. The weighting coefficient of the control effort square, which is the second term of the reward shown in (8), was 0.01. From Fig.…”

Section: Application To Spherical Actuatormentioning

confidence: 99%

“…Next, the weighting coefficient of the control effort square, which is the second term in the reward shown in (8), was examined. The control effort square coefficient was changed up to 2 and examined.…”

Section: Application To Spherical Actuatormentioning

confidence: 99%

“…Moreover, the applicability of the actuator to a precision robot was shown. The computation accuracy of dynamic torque characteristics was evaluated [8].…”

Section: Introductionmentioning

confidence: 99%

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Robust control of three‐degree‐of‐freedom spherical actuator based on deep reinforcement learning

Fusayasu

Heya

Hirata

2022

IEEJ Transactions Elec Engng

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Multi‐degree‐of‐freedom (multi‐DOF) spherical actuators have been developed for the fields of robotics and industrial machineries. We have proposed an outer rotor type three‐DOF spherical actuator that can realize a high torque density. Each coil input current is calculated using a torque generating equation based on the torque constant matrix. The permanent magnet type actuators have a problem with generating unexpected cogging torque due to various manufacturing errors. Manufacturing errors mainly mean differences between the ideal dimensions at the motor design stage and the actual dimensions in mass production. In this case, the actuator would exceed the limitations of classical proportional‐integral‐differential (PID) controllers. Therefore, we propose a current compensator using reinforcement learning by introducing a deep neural network that is expected to improve the robustness of spherical actuators. This current compensator was applied to uncertainty problems such as manufacturing fluctuations of cogging torque. We examined the reward, which is the main parameter of deep reinforcement learning, and reduced the control error compared to classical PID controller and simple neural network (NN) controller. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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“…12. The weighting coefficient of the control effort square, which is the second term of the reward shown in (8), was 0.01. From Fig.…”

Section: Application To Spherical Actuatormentioning

confidence: 99%

Section: Application To Spherical Actuatormentioning

confidence: 99%

See 1 more Smart Citation

Robust control of three‐degree‐of‐freedom spherical actuator based on deep reinforcement learning

Fusayasu

Heya

Hirata

2022

IEEJ Transactions Elec Engng

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“…However, due to the specific set of magnets used, the movable angle along the Z-axis was only ±5 • . Chu et al, Fusayasu et al, and Yang et al also proposed other spherical VCMs of this type [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Design and Simulation of Novel 3-DOF Spherical Voice Coil Motor

2021

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Multi-DOF motion is realized in the eyes and joints of robots mostly through the combination of multiple one-degree-of-freedom (1-DOF) motors. However, this results in reduced efficiency, a large volume, reduced response speed, and inaccurate positioning. To solve these problems, this study proposes a novel 3-DOF spherical voice coil motor (VCM). In this VCM, 16 coils and a radially oriented ring magnet are used to generate a Lorentz force to achieve motion. In particular, coils for Z-axis rotation are sandwiched between the coils for X- and Y-axis rotation. Furthermore, the proposed VCM can achieve 360° rotation about the Z-axis. The commercial software ANSYS was used to design and verify the performance of the proposed VCM. Simulation results indicate that this VCM affords improved power efficiency because only a suitable combination of coils, rather than all coils, needs to be powered on. The results demonstrate the feasibility of the proposed 3-DOF spherical VCM.

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“…Spherical motors are electric devices capable of achieving multiple DOF rotary motions in a single joint [19][20][21]. Spherical motors have several advantages, such as a compact structure, a flexible motion mode, no accumulation of motion bias, and a simple control method compared with conventional multi-DOF actuating systems that consist of several single-DOF motors [1,22,23]. Therefore, they have been actively developed and have a wide application prospect in joints and eyeballs of the humanoid, unmanned aerial vehicles, autonomous cars, walking robots, and other fields.…”

Section: Introductionmentioning

confidence: 99%

Analytical Investigation on Torque of Three-Degree-of-Freedom Electromagnetic Actuator for Image Stabilization

2021

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In keeping with consumers’ preferences for electromagnetic motors of ever smaller power consumption, it is necessary to improve the power efficiency of the electromagnetic motors used in unmanned aerial vehicles and robots without sacrificing their performance. Three-degree-of-freedom (3-DOF) spherical motors have been developed for these applications. Accordingly, this study modifies the 3-DOF spherical motor proposed by Hirata’s group in a previous study (Heya, A.; Hirata, K.; Niguchi, N., Dynamic modeling and control of three-degree-of-freedom electromagnetic actuator for image stabilization, IEEE Transactions on Magnetics 2018, 54, 8207905.) to accomplish a 3-DOF spherical motor for camera module with higher torque output in the large rotation angle. The main contribution of this study is to improve the static torque in the X- and Y-axes with an improved electromagnetic structure and a particular controlling strategy. In the structural design, eight symmetrical coils with specific coil combination are used instead of conventional four symmetrical coils. In this study, the development of the proposed 3-DOF spherical motor was constructed and verified by using a 3D finite-element method (3D FEM). The simulation results show that the proposed 3-DOF spherical motor has higher torque output in the large rotation angle when compared to the original 3-DOF spherical motor.

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Analysis Accuracy in Positioning Calculation for Three-Degree-of-Freedom Spherical Actuator

Cited by 8 publications

References 7 publications

Robust control of three‐degree‐of‐freedom spherical actuator based on deep reinforcement learning

Robust control of three‐degree‐of‐freedom spherical actuator based on deep reinforcement learning

Design and Simulation of Novel 3-DOF Spherical Voice Coil Motor

Analytical Investigation on Torque of Three-Degree-of-Freedom Electromagnetic Actuator for Image Stabilization

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