Simulating LQR and PID controllers to stabilise a three-link robotic system

Mohamed, Mahmoud; Anayi, Fatih; Packianather, Michael; Samad, Bdereddin Abdul; Yahya, Khalid

doi:10.1109/icacite53722.2022.9823512

Cited by 10 publications

(11 citation statements)

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“…Earlier studies have provided extensive information on independent swing-up motion for triple-link robots, and especially for robots using a single unactuated and 2 actuated joints, including for example those reported in [11][12][13][14][15] The main focus of such work has been on designing and implementing various types of controllers to operate the Robogymnast, which is a triple-link system with a pendulum action. In addition, these studies have investigated the problem of stabilising multiple-link robots using swinging mechanisms, again through different controller designs, : e.g., LQR [1] PID [16] Fuzzy-PD [17] and FLQR [18] and LQR-PID [19]. Moreover, prior work has investigated problems of motion in people who have restricted or impaired limb motion due to injury or disability [20].…”

Section: Related Workmentioning

confidence: 99%

“…The hybrid FLQR controller developed here is a combination of an optimised LQR control and a rules-based fuzzy control system [16]. FLC systems centrally utilise Fuzzy Control Rules (FCRs) linked together with fuzzy implications as well as the compositional rule of inference key component of an FLC system is a set of Fuzzy Control Rules (FCRs) that are connected through a fuzzy implication and the compositional rule of inference [17].…”

Section: Control Designmentioning

confidence: 99%

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Enhanced the Control Strategy of a Triple Link Robotic System (Robogymnast)

2023

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This research aims to optimise performance in a Fuzzy Linear Quadratic Regulator controller by implementing 2 types of algorithm to stabilise the triple-link 'Robogymnast' robotic system. The Robogymnast recreates the movements of a human gymnast, with the hand/arm element of the system securely attached to a high bar with ball0bearing mountings, which can rotate freely. This article explores the complex factors involved in swing-up control in the underactuated Robogymnast and presents a linearisation of the mathematical modelling for the system, considering methods which apply Lagrangian equations in defining state space in such systems. Both the Teaching-Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO) algorithm were used for tuning the hybrid Fuzzy Linear Quadratic Regulator controller for later application with the robot and assessment of response stability. In addition, MATLAB Simulink was used to simulate performance and show the effect of altering parameters including time for rising, settling and overshoot. This work aims primarily to explore how a Linear Quadratic Regulator/Fuzzy Logic controller can be applied with acrobatic robots.

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Section: Related Workmentioning

confidence: 99%

Section: Control Designmentioning

confidence: 99%

Enhanced the Control Strategy of a Triple Link Robotic System (Robogymnast)

2023

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“…• Examining motion problems for individuals who have issues with limb function due to disability or injury [3][4][5][6].…”

Section: Related Workmentioning

confidence: 99%

“…• Effectively controlling such systems through the exploitation of their intrinsic dynamic parameters to facilitate more energy-efficient design for machines by attaining smooth motions more similar to naturally occurring mechanisms for movement [3][4][5][6]. • Developing modelling, simulations and control of underactuated systems to lead to a more in-depth understanding of currently available control applications and optimising their applications to benefit industry and society more generally [5].…”

Section: Related Workmentioning

confidence: 99%

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Analysing Various Control Technics for Manipulator Robotic System (Robogymnast)

Mahmoud¹,

Samad²,

Anayi³

et al. 2023

Computers, Materials &Amp; Continua

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The Robogymnast is a highly complex, three-link system based on the triple-inverted pendulum and is modelled on the human example of a gymnast suspended by their hands from the high bar and executing larger and larger upswings to eventually rotate fully. The links of the Robogymnast correspond respectively to the arms, trunk, and lower limbs of the gymnast, and from its three joints, one is under passive operation, while the remaining two are powered. The passive top joint poses severe challenges in attaining the smooth movement control needed to operate the Robogymnast effectively. This study assesses four types of controllers used for systems operation and identifies how far response stabilisation is achieved with each. The system is simulated using MATLAB Simulink, with findings generated regarding rising and settling time, as well as overshoot. The research primarily seeks to examine the application of a linear quadratic regulator controller, proportionalintegral-derivative controller, fuzzy linear quadratic regulator controller and linear quadratic regulator-proportional-integral-derivative controller for this type of system and comparisons between the different controllers to demonstrate successful performance, which highlights the claimed advantages of the proposed system.

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