Integral Criterion-Based Adaptation Control to Vibration Reduction in Sensitive Actuators

Vosoogh, Mahmood; Piltan, Farzin; Mirshekaran, Abdol Majid; Barzegar, Ali; Siahbazi, Alireza; Sulaiman, Nasri

doi:10.14257/ijhit.2015.8.2.02

Cited by 3 publications

(6 citation statements)

References 16 publications

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“…An alternative way to solve the chattering problem is the application of the fuzzy logic [12] in the construction of the control input. Fuzzy logic has proven to be a potent tool in the sliding mode control of time-invariant linear systems [13][14][15][16][17][18][19][20][21][22] as well as timevarying nonlinear systems [14]. It provides methods for formulating linguist rules from expert knowledge and is able to approximate any real continuous system to arbitrary accuracy.…”

Section: Figure 1 Dental Robot Manipulatormentioning

confidence: 99%

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Design Active Intelligent Multi Degrees of Freedom Joint Controller for Dental Automation

Rahmani¹,

Sobhani²,

Cheraghi³

et al. 2015

IJHIT

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Following the developments in industrial robot technology, robotics has found its way into the medical field and is used in a range of surgical disciplines. The main purpose of the use of robots is to increase the precision, quality and safety of surgical procedures. Robotics is not yet used in dentistry even though all the necessary technologies have already been developed and could easily be adapted. Some of the technologies are already used in dentistry, such as image-based simulation of implant surgery followed by the use of surgical guides, and creating digital impressions of pre parathions using an intra-oral scanner, after which a milling device produces the restoration, but we have not yet seen any robot able to prepare teeth for crowns, inlays or bridges. Such a robot would fundamentally be a dental drilling device coupled with a navigation device to determine the correct position of the device in relation to the patient. However this technique is very essential to have the minimal pain and reduce bleeding but control of these robots/joints are very complicated. This paper proposes new fuzzy type sliding mode controller for multi-DOF joints to control of motor vibration. The fuzzy (PD+I) 2 single-input single-output (SISO) fuzzy system is used to control of chattering in sliding mode controller. In most research al researchers wants to eliminate the chattering but, this research focuses on chattering control. Various operation situations such as the set point control and the trajectory control are simulated. The simulation results demonstrate that the chattering and the steady state errors, which usually occur in the classical sliding mode control, are limitation control and satisfactory trajectory tracking is achieved.

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Section: Figure 1 Dental Robot Manipulatormentioning

confidence: 99%

“…Mohan and Bhanot have addressed comparative study between some adaptive fuzzy and a new hybrid fuzzy control algorithm for manipulator control. They found that self-organizing fuzzy logic controller and proposed hybrid integrator fuzzy give the best performance as well as simple structure [18][19][20][21][22].…”

Section: Figure 1 Dental Robot Manipulatormentioning

confidence: 99%

Design Active Intelligent Multi Degrees of Freedom Joint Controller for Dental Automation

Rahmani¹,

Sobhani²,

Cheraghi³

et al. 2015

IJHIT

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show abstract

“…Uncertainty in system can causes some problems about dentistry. To solve this problem, neural network, fuzzy logic, and neurofuzzy are synergically combined with classical controller and used in nonlinear, time variant, and uncertainty plant (e.g., robot) [14][15][16][17][18][19][20].…”

Section: Figure 2 Intuitive Surgical Davinci Surgical Systemmentioning

confidence: 99%

“…The current number of researchers in this field and research societies mushrooming around the world show the attractiveness of this theory for both theoretical and practical researchers. One of the newest and most challenging technological applications is of the fuzzy logic in the control system of a dental robot, which is fundamentally unstable and with highly nonlinear dynamics [16][17][18][19][20]. In this research the main target is design PID intelligent controller to improve the robust, stability and reliability in dental robot manipulator.…”

Section: Figure 2 Intuitive Surgical Davinci Surgical Systemmentioning

confidence: 99%

“…The second step is implementing the Coriolis and Centrifugal matrix which they can calculate by partial derivatives of kinetic energy. The last step to implement the dynamic equation of robot manipulator is to find the gravity vector by performing the summation of Lagrange's formulation [19][20].…”

Section: Theorem: Case Study (Dynamic Formulation Of Robot Manipulator)mentioning

confidence: 99%

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Design Active Robot Controller for Dental Automation

Piltan¹,

Yekband²,

Mirzaie³

et al. 2015

IJUNESST

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Deep Reinforcement Learning-Based Adaptive Controller for Trajectory Tracking and Altitude Control of an Aerial Robot

Barzegar

Lee

2022

Applied Sciences

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This research study presents a new adaptive attitude and altitude controller for an aerial robot. The proposed controlling approach employs a reinforcement learning-based algorithm to actively estimate the controller parameters of the aerial robot. In dealing with highly nonlinear systems and parameter uncertainty, the proposed RL-based adaptive control algorithm has advantages over some types of standard control approaches. When compared to the conventional proportional integral derivative (PID) controllers, the results of the numerical simulation demonstrate the effectiveness of this intelligent control strategy, which can improve the control performance of the whole system, resulting in accurate trajectory tracking and altitude control of the vehicle.

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Integral Criterion-Based Adaptation Control to Vibration Reduction in Sensitive Actuators

Abstract: Refer to this research, an integral criterion-based hybrid

Cited by 3 publications

References 16 publications

Design Active Intelligent Multi Degrees of Freedom Joint Controller for Dental Automation

Design Active Intelligent Multi Degrees of Freedom Joint Controller for Dental Automation

Design Active Robot Controller for Dental Automation

Deep Reinforcement Learning-Based Adaptive Controller for Trajectory Tracking and Altitude Control of an Aerial Robot

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