Velocity control of mobile wheeled inverted pendulum

Mao, Lifei; Huang, Jian; Ding, Feng; Wang, Yongji

doi:10.1504/ijmic.2013.054036

Cited by 7 publications

(3 citation statements)

References 17 publications

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“…In order to model the system mathematically, Lagrangian method is used (Mao et al, 2013;He et al, 2015). This method is based on the principle of conservation of mechanical energy.…”

Section: Mathematical Modelling Of the Inverted Pendulummentioning

confidence: 99%

Modelling and predictive control of an inverted pendulum system by MLD approach: multivariable case

Saidi

Hammi

Douik

2017

IJMIC

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This paper deals with a class of hybrid systems that is presented by mixed logical dynamical (MLD) formalism. This approach is well-adapted to hybrid systems, particularly because of its ability not only to model systems involving continuous and discrete dynamics under constraints, but also to address several issues such as model predictive control (MPC) of this class of systems. This approach will be illustrated by the multivariable modelling of the inverted pendulum system. Therefore, the resultant system is well-posed for MPC strategy. Simulations were effected using the HYSDEL compiler to illustrate the efficiency of this formalism.

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“…In order to model the system mathematically, Lagrangian method is used (Mao et al, 2013;He et al, 2015). This method is based on the principle of conservation of mechanical energy.…”

Section: Mathematical Modelling Of the Inverted Pendulummentioning

confidence: 99%

Modelling and predictive control of an inverted pendulum system by MLD approach: multivariable case

Saidi

Hammi

Douik

2017

IJMIC

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“…These systems are testing bed platforms for comparing various control algorithms and strategies (Kizir et al, 2010;Henmi et al, 2015). The system resembles dynamics of humanoid robot, flexible space structures and therefore attracts interest of many researchers (Mao et al, 2013;Eltohamy and Kuo, 2010). Farwig and Unbehauen (1990) examined stabilisation of triple link inverted pendulum based on state space approach.…”

Section: Introductionmentioning

confidence: 99%

Lenient computation in controlling the nonlinear system based on adaptive error optimisation in microgrid

Yuvaraja¹,

Ramya²

2018

IJIMR

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This manuscript describes the hybrid learning algorithm for training the error optimisation in an MIMO nonlinear system. The automated controller is designed using lenient computation technique with a Levenberg-Marquardt training algorithm. The designed controller is interfaced to a microgrid which has renewable energy sources like solar, wind, fuel cell, or smart battery as input and the output power generated by these sources can be utilised for various grid and atomised applications. The erudition capability and designing methodology of adaptive networks and sturdiness of PID controllers are described. Finally, the study illustrates an offline mode comparison of PID-based ANFIS and neural controllers in terms of settling time, steady state error and overshoot.

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“…An inverted pendulum type mobile robot is a system that adds mobility to the utilization of a mechanical function to balance the inverted pendulum system [1]. Research related to the control of an inverted pendulum type system has been widely reported [2][3][4][5][6][7][8][9][10][11][12][13]. Furthermore, it is similar to the control scheme of a biped robot created based on the observation that people maintain balance using their two feet while moving to a destination.…”

Section: Introductionmentioning

confidence: 99%

Design of Simple-Structured Fuzzy Logic Systems for Segway-Type Mobile Robot

Yoo

Choi

2015

Int. J. Fuzzy Log. Intell. Syst.

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Studies on the control of the inverted pendulum type system have been widely reported. This is because it is a typical complex nonlinear system and may be a good model for verifying the performance of a proposed control system. In this paper, we propose the design of some fuzzy logic control (FLC) systems for controlling a Segway-type mobile robot, which is an inverted pendulum type system. We first derive a dynamic model of the Segway-type mobile robot and then analyze it in detail. Next, we propose the design of some FLC systems that have good performance for the control of any nonlinear system. Then, we design two conventional FLC systems for the position and balance control of the Segway-type mobile robot, and we demonstrate their usefulness through simulations. Next, we point out the possibility of simplifying the design process and reducing the computational complexity,, which results from the skew symmetric property of the fuzzy control rule tables. Finally, we design two other FLC systems for position and balance control of the Segway-type mobile robot. These systems have only one input variable in the FLC systems. Furthermore, we observe that they offer similar control performance to that of the conventional two-input FLC systems.

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Velocity control of mobile wheeled inverted pendulum

Cited by 7 publications

References 17 publications

Modelling and predictive control of an inverted pendulum system by MLD approach: multivariable case

Modelling and predictive control of an inverted pendulum system by MLD approach: multivariable case

Lenient computation in controlling the nonlinear system based on adaptive error optimisation in microgrid

Design of Simple-Structured Fuzzy Logic Systems for Segway-Type Mobile Robot

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