Design PID Baseline Fuzzy Tuning Proportional- Derivative Coefficient Nonlinear Controller with Application to Continuum Robot

Yazdanpanah, Azita; Piltan, Farzin; Roshanzamir, Ali; Mirshekari, Marjan; Mozafari, Narges Gholami

doi:10.5815/ijisa.2014.05.10

Cited by 7 publications

(7 citation statements)

References 34 publications

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“…This system can move towards any direction properly. The wireless camera to transmit [21] video has worked as the instruction given to it. The video transmission and all the sensors in this system are performing accurately.…”

Section: Resultsmentioning

confidence: 99%

Smartphone Controlled Spy Robot with Video Transmission and Object Collector

Hasan¹,

Jewel²,

Mostakim³

et al. 2017

IJEM

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Android, an operating system developed by Google for smartphones, tablets and such type of touchscreen phones. Android app is a software running on Android platform. Typically an app is designed for specific purpose on Android platform such as smartphones and tablets. In this work a designing and implementing process of an Android based spy robot is described. An Android based application, RC Bluetooth controller is used to control in this spy robot. This robot can be controlled with the help an app of Android phones. Arduino based microcontroller is used for instruction processing and giving proper instructions. Bluetooth technology is used to interface between Arduino and Android. A hand for collecting and holding objects and a camera for live video steaming is used to observe any object & movement of robot. This robot can move to any place and perform smartly within Bluetooth network range.

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Section: Resultsmentioning

confidence: 99%

Smartphone Controlled Spy Robot with Video Transmission and Object Collector

Hasan¹,

Jewel²,

Mostakim³

et al. 2017

IJEM

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show abstract

“…The dynamic modeling describes the relationship between joint motion, velocity, and accelerations to force/torque or current/voltage and also it can be used to describe the particular dynamic effects (e.g., inertia, coriolios, centrifugal, and the other parameters) to behavior of system [1]. The equation of an n-DOF robot manipulator governed by the following equation [1,4,[22][23][24]:…”

Section: Dynamic Formulation Of 2-dof Robot Manipulatormentioning

confidence: 99%

“…This robot manipulator dynamic equation can also be written in a following form [20][21][22][23][24][25]:…”

Section: Dynamic Formulation Of 2-dof Robot Manipulatormentioning

confidence: 99%

“…This controller works very well when all dynamic and physical parameters are known but when the robot manipulator has variation in dynamic parameters, the controller has no acceptable performance [18][19][20]. In practice, most of physical systems (e.g., robot manipulators) parameters are unknown or time variant, therefore, computed torque like controller used to compensate dynamic equation of robot manipulator [21][22][23][24][25] [13]. The main reasons to use fuzzy logic methodology are able to give approximate recommended solution for uncertain and also certain complicated systems to easy understanding and flexible.…”

Section: Introductionmentioning

confidence: 99%

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Design Adaptive Fuzzy Inference Controller for Robot Arm

Mirzadeh¹,

Haghighi²,

Khezri³

et al. 2014

IJITCS

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Abstract-Design robust controller for uncertain nonlinear systems most of time can be a challenging work. One of the most active research areas in this field is control of the robot arm. The control strategies for robotics are classified in two main groups: classical and non-classical methods, where the classical methods use the conventional control theory and nonclassical methods use the artificial intelligence theory such as fuzzy logic, neural networks and/or neuro-fuzzy. Control robot arm using classical controllers are often having lots of problems because robotic systems are always highly nonlinear. Accurate robot manipulator is difficult because some dynamic parameters such as compliance and friction are not well understood and some robot parameters such as inertia are difficult to measure accurately. Artificial control such as Fuzzy logic, neural network, genetic algorithm, and neurofuzzy control have been applied in many applications. Therefore, stable control of a nonlinear dynamic system such as a robot arm is challenging because of some mentioned issues. In this paper the intelligent control of robot arm using Adaptive Fuzzy Gain scheduling (AFGS) and comparison to fuzzy logic controller (FLC) and various performance indices like the RMS error, and Steady state error are used for test the controller performance.

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“…Although the fuzzy-logic control is not a new technique, its application in this current research is considered to be novel since it aimed for an automated dynamic-less response rather than for the traditional objective of uncertainties compensation [38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55]. The intelligent tracking control using the fuzzy-logic technique provides a cost-and-time efficient control implementation due to the automated dynamic-less input.…”

Section: Introductionmentioning

confidence: 99%

Design New PID like Fuzzy CTC Controller: Applied to Spherical Motor

Shamsodini¹,

Piltan²,

Rahbar³

et al. 2014

IJMECS

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Abstract-The minimum rule base Proportional Integral Derivative (PID) Fuzzy Computed Torque Controller with application to spherical motor is presented in this research. The popularity of PID Fuzzy Computed Torque Controller can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. PID methodology has three inputs and if any input is described with seven linguistic values, and any rule has three conditions we will need 343 rules. It is too much work to write 343 rules and have lots of problem to design embedded control system e.g., Field Programmable Gate Array (FPGA). In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PD-like fuzzy controller and a conventional PI controller to have the minimum rule base and acceptable trajectory follow disturbance to control of spherical motor. However computed torque controller is work based on cancelling decoupling and nonlinear terms of dynamic parameters for each direction of three degree of freedom spherical motor, this controller is work based on motor dynamic model and this technique is highly sensitive to the knowledge of all parameters of nonlinear spherical motor"s dynamic equation. This research is used to reduce or eliminate the computed torque controller problem based on minimum rule base fuzzy logic theory to control of three degrees of freedom spherical motor system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.Index Term-PID like fuzzy control, computed torque controller, PD like fuzzy control, conventional PI control, three degrees of freedom spherical motor.

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Design PID Baseline Fuzzy Tuning Proportional- Derivative Coefficient Nonlinear Controller with Application to Continuum Robot

Cited by 7 publications

References 34 publications

Smartphone Controlled Spy Robot with Video Transmission and Object Collector

Smartphone Controlled Spy Robot with Video Transmission and Object Collector

Design Adaptive Fuzzy Inference Controller for Robot Arm

Design New PID like Fuzzy CTC Controller: Applied to Spherical Motor

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