Fuzzy adaptive PI control of omni-directional mobile robot

Sheikhlar, Arash; Fakharian, Ahmad; Adhami-Mirhosseini, Aras

doi:10.1109/ifsc.2013.6675667

Cited by 9 publications

(3 citation statements)

References 9 publications

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“…In the work of Salhi and Alimi (2013 ) a similar idea is implemented using point cloud and low cost depth sensor. A fuzzy PI version is presented in the work of Sheikhlar, Fakharian, and Adhami-Mirhosseini (2013 ) where fuzzy inference rules were established by using the tracking error and its derivative. Also, the advances in fuzzy fractional calculus ( Taka či, Taka či, & Taka či, 2014 ) have allowed its use in fuzzy PID control of mobile robots applications to offer more flexible designs ( Liu, Pan, & Xue, 2015;Shah & Agashe, 2016;Sharma, Rana, & Kumar, 2014 ).…”

Section: Related Workmentioning

confidence: 99%

Incremental Q -learning strategy for adaptive PID control of mobile robots

Carlucho

Paula

Villar

et al. 2017

Expert Systems with Applications

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Section: Related Workmentioning

confidence: 99%

Incremental Q -learning strategy for adaptive PID control of mobile robots

Carlucho

Paula

Villar

et al. 2017

Expert Systems with Applications

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“…Something similar was proposed in [13], where a fuzzy controller was used to control the speed and direction of an intelligent mobile robot that tracked and obtained the trajectory of a specific target. While in [14], a fuzzy adaptive PI controller for the non-linear control of the motion of a four-wheeled omnidirectional mobile robot was employed, the fuzzy adaptive algorithm adjusted the PI controller's parameters, and the fuzzy inference rules were set using the tracking error and its derivative.…”

Section: Introductionmentioning

confidence: 99%

Proposal of a Decoupled Structure of Fuzzy-PID Controllers Applied to the Position Control in a Planar CDPR

et al. 2021

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The design of robot systems controlled by cables can be relatively difficult when it is approached from the mathematical model of the mechanism, considering that its approach involves non-linearities associated with different components, such as cables and pulleys. In this work, a simple and practical decoupled control structure proposal that requires practically no mathematical analysis was developed for the position control of a planar cable-driven parallel robot (CDPR). This structure was implemented using non-linear fuzzy PID and classic PID controllers, allowing performance comparisons to be established. For the development of this research, first the structure of the control system was proposed, based on an analysis of the cables involved in the movement of the end-effector (EE) of the robot when they act independently for each axis. Then a tuning of rules was carried out for fuzzy PID controllers, and Ziegler–Nichols tuning was applied to classic PID controllers. Finally, simulations were performed in MATLAB with the Simulink and Simscape tools. The results obtained allowed us to observe the effectiveness of the proposed structure, with noticeably better performance obtained from the fuzzy PID controllers.

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“…Several Control approaches and optimal trajectory planning of omni-directional wheeled robots have been reported in [4][5][6]. In [7], fuzzy adaptive PI has been tested in simulations. In [8], a delay compensator fuzzy tracking algorithm has been developed for the robots.…”

Section: Introductionmentioning

confidence: 99%

Adaptive optimal control via reinforcement learning for omni-directional wheeled robots

Sheikhlar

Fakharian

2016

2016 4th International Conference on Control, Instrumentation, and Automation (ICCIA)

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The main problem of wheeled soccer robots is the low level controller gains regulation particularly in competition. The low level control task is tracking the desired angular velocities of the robot wheels which are generated by the high level controller. Since the robot's model and environment have many uncertainties, traditional controller gains must be adjusted before every match along the competition. In this paper, a linear quadratic tracking (LQT) scheme is designed to solve this problem. The controller can regulate the parameters on-line by policy iteration reinforcement learning algorithm. The output paths of the four-wheeled soccer robot with the adaptive LQT are compared with traditional LQT and the results show that the proposed method can provide superior performance in presence of uncertainties and nonlinearities.

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Fuzzy adaptive PI control of omni-directional mobile robot

Cited by 9 publications

References 9 publications

Incremental Q -learning strategy for adaptive PID control of mobile robots

Incremental Q -learning strategy for adaptive PID control of mobile robots

Proposal of a Decoupled Structure of Fuzzy-PID Controllers Applied to the Position Control in a Planar CDPR

Adaptive optimal control via reinforcement learning for omni-directional wheeled robots

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