Fuzzy Immune PD Algorithm Applied in the Self-Balancing Two-Wheeled Robot

Wang, Qingcheng; Fang, Jian

doi:10.1109/fgcn.2014.35

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Figure 3 shows the state-feedback controller of the TWIP robot. For PD controller of angle, (9) The closed-loop transfer function,…”

Section: State-feedback Controllermentioning

confidence: 99%

“…QingchengandJian [8]designed a fuzzy immune PD controller to achieve self-balance of TWIP and compared its performance with those of conventional fuzzy PD controller. Sadeghian and Masoulethey [9] designed three controllers to balance the TWIP, PD controller, PID controller and Fuzzy-PID. Controller's parameters were tuned with the Genetic Algorithm and fuzzy logic.…”

Section: Introductionmentioning

confidence: 99%

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Conventional Fuzzy Logic Controller for Balancing Two-Wheel Inverted Pendulum

Abd-elaziz

2020

Journal of Advanced Engineering Trends

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This paper presents the design and the Real-Time implementation of self-balancing Two-Wheeled Inverted Pendulum (TWIP) using state-feedback controller and a conventional fuzzy logic controller (CFLC) on Real-Time. The state-feedback controller consists of two parts PD controller and PI controller. The state-feedback controller was designed first for the nonlinear model then it was updated for the Real-Time implementation. The CFLC was designed first based on the state-feedback controller to reach the point of using pure fuzzy controller for the TWIP. The CFLC was designed with Mamdani fuzzy inference architecture if-then rules. The TWIP is balanced with CFLC with a base of 7 rules only. Different controller's types were tested on real-Time to perform a good balance for the TWIP. Fuzzy PI, Fuzzy PD, and combination of two independent CFLC were used to achieve the balancing of the TWIP on Real-Time.

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“…Figure 3 shows the state-feedback controller of the TWIP robot. For PD controller of angle, (9) The closed-loop transfer function,…”

Section: State-feedback Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Conventional Fuzzy Logic Controller for Balancing Two-Wheel Inverted Pendulum

Abd-elaziz

2020

Journal of Advanced Engineering Trends

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Real-time Mamdani-like fuzzy and fusion-based fuzzy controllers for balancing two-wheeled inverted pendulum

Moness

Mahmoud

Hussein

2020

J Ambient Intell Human Comput

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Hierarchical optimization for Whole-Body Control of Wheeled Inverted Pendulum Humanoids

Zafar

Hutchinson

Theodorou

2019

2019 International Conference on Robotics and Automation (ICRA)

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In this paper, we present a whole-body control framework for Wheeled Inverted Pendulum (WIP) Humanoids. WIP Humanoids are redundant manipulators dynamically balancing themselves on wheels. Characterized by several degrees of freedom, they have the ability to perform several tasks simultaneously, such as balancing, maintaining a body pose, controlling the gaze, lifting a load or maintaining end-effector configuration in operation space. The problem of whole-body control is to enable simultaneous performance of these tasks with optimal participation of all degrees of freedom at specified priorities for each objective. The control also has to obey constraint of angle and torque limits on each joint. The proposed approach is hierarchical with a low level controller for body joints manipulation and a high-level controller that defines center of mass (CoM) targets for the low-level controller to control zero dynamics of the system driving the wheels. The low-level controller plans for shorter horizons while considering more complete dynamics of the system, while the high-level controller plans for longer horizon based on an approximate model of the robot for computational efficiency.

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Fuzzy Immune PD Algorithm Applied in the Self-Balancing Two-Wheeled Robot

Cited by 3 publications

References 6 publications

Conventional Fuzzy Logic Controller for Balancing Two-Wheel Inverted Pendulum

Conventional Fuzzy Logic Controller for Balancing Two-Wheel Inverted Pendulum

Real-time Mamdani-like fuzzy and fusion-based fuzzy controllers for balancing two-wheeled inverted pendulum

Hierarchical optimization for Whole-Body Control of Wheeled Inverted Pendulum Humanoids

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