Iterative Learning Control for V-Shaped Electrothermal Microactuator

Dzung, Nguyen Tien; Phuc, Pham Hong; Nguyen, Quang Dich; Phuoc, Nguyen Doan

doi:10.3390/electronics8121410

Cited by 6 publications

(3 citation statements)

References 31 publications

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“…where F b is the thermal expansion force generates along the single beam; A is the area of the beam cross-section; Dl is the total thermal expansion along the length l b of single beam; a l is a thermal expansion coefficient of silicon; and E = 1.69 Â 10 5 (Mpa) is the silicon Young's modulus. Displacement of the beam tip B (called Dd i ) is described in Figure 3 (Nguyen et al, 2019).…”

Section: Thermal Expansion Forcementioning

confidence: 99%

Improving displacement of silicon V-shaped electrothermal microactuator using platinum sputter deposition process

Nam

Pham²,

Hoang³

2023

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Purpose This paper aims to propose a method to reduce the resistance of silicon-based V-shaped electrothermal microactuator (VEM) by applying a surface sputtering process. Design/methodology/approach Four VEM’s samples have been fabricated using traditional silicon on insulator (SOI)-Micro-electro-mechanical System (MEMS) technology, three of them are coated with a thin layer of platinum on the top surface by sputtering technique with different sputtered times and the other is original. The displacements of the VEM are calculated and simulated to evaluate the advantages of sputtering method. Findings The measured results show that the average resistance of the sputtered structures is approximately 1.16, 1.55 and 2.4 times lower than the non-sputtering sample corresponding to the sputtering time of 1.5, 3 and 6 min. Simulation results confirmed that the maximum displacement of the sputtered VEM is almost 1.45 times larger than non-sputtering one in the range of voltage from 8 to 20 V. The experimental displacements are also measured to validate the better performance of the sputtered samples. Originality/value The experimental results demonstrated the better displacement of the VEM structure after using the platinum sputtering process. The improvement can be considered and applied for enhancing displacement as well as decreasing the driving voltage of the other electrothermal microactuators like U- or Z-shaped structures while combining with the low-cost SOI-MEMS micromachining technology.

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Section: Thermal Expansion Forcementioning

confidence: 99%

Improving displacement of silicon V-shaped electrothermal microactuator using platinum sputter deposition process

Nam

Pham²,

Hoang³

2023

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“…MATLAB/simscape multibody provides a powerful quasi-physical simulation environment for multi-component mechanical systems such as robots, multibody systems, hydraulic and pneumatic systems. The simscape-based approach has been exploited successfully in several studies, e.g., [27]- [29]. Simscape multibody gives blocks representing links, joints, sensors, and torque/force components that make the simscape-based model conformable to the actual robot.…”

Section: Simscape-based Quasi-physical Modeling Of the Robotmentioning

confidence: 99%

Impact analysis of actuator torque degradation on the IRB 120 robot performance using simscape-based model

Truc

Quang

2021

IJECE

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Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.

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“…It has the ability to learn, memorize and improve the quality in the next cycle. They have been very successfully applied in the robotics industry [13]- [16], calculating for CNC machines [17], moving wafers [18]- [20], injection molding machines [21], [22], metal casting machines [23], [24], cold rolling mills [25], [26], electromechanical valve actuator [27]- [29], locking brakes [30], [31], a Class of Distributed Parameter System [32]- [34] and many other fields [35]- [45].…”

Section: Introductionmentioning

confidence: 99%

Proportional Derivative – Type Iterative Learning Algorithm for a Motion Control System

Huyen

Hoc

Hoa

2023

IJRCS

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In this paper, Iterative Learning Control (ILC) combined with a Proportional Derivative (PD) regulator is proposed to deal with the problem of designing a control signal for motion control systems. The main idea in iterative learning control is to gradually improve the performance of the system by exploiting data from the previous iterations. The learning control algorithm can obtain a better tracking control performance for the next run and hence outperforms conventional control approaches such as Proportional Integral Derivative (PID) controller and feedforward control. The main area of application for ILC is control of industrial robots and CNC machine tool, printing, and other industrial applications. The learning algorithms can also be used in combination with other control techniques. For example, learning feedforward control is designed in the first iteration. Then iterative learning control is applied to improve performance in the subsequent iterations. In addition, the conventional feedback regulator is designed in combination with iterative control to deal with uncertainty. Simulation results demonstrate the potential benefits, sensitivity and robustness of the proposed method.

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Iterative Learning Control for V-Shaped Electrothermal Microactuator

Cited by 6 publications

References 31 publications

Improving displacement of silicon V-shaped electrothermal microactuator using platinum sputter deposition process

Improving displacement of silicon V-shaped electrothermal microactuator using platinum sputter deposition process

Impact analysis of actuator torque degradation on the IRB 120 robot performance using simscape-based model

Proportional Derivative – Type Iterative Learning Algorithm for a Motion Control System

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