Motion Control of Triple Links Inverted Pendulum on Two-Wheeled System Using Interval Type-2 Fuzzy Logic Control Base on Particle Swarm Optimization

Masrom, M. F.; Ghani, Nor Maniha Abdul; Jamin, N. F.; Razali, Noorhelyna

doi:10.1109/iccsce47578.2019.9068536

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…Huang et al [7] applied optimal LQR based on motion vision to stabilize the triple inverted pendulum, Banijamali et al [8] proposed a model for learning robust locally-linear controllable embedding (RCE) for prediction and planning, Masrom et al [9] applied IT2FLC based on PSO to control the motion of the triple inverted pendulum. All of these researches focused on noise effect on the system only.…”

Section: Introductionmentioning

confidence: 99%

Balancing of Robustness and Performance for Triple Inverted Pendulum Using μ-Synthesis and Gazelle Optimization

Shafeek,

Ali

2024

JESA

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The control of systems like: bipedal locomotion robots, space launch vehicle, offshore wind turbines, and active vibration control systems in buildings and bridges, have to ensure, besides stability and accuracy, the system's insensitivity to parameters' uncertainties, unmodeled dynamics, external disturbances, and measurements noise. In such systems analysis and controller design, a triple inverted pendulum can be used as a benchmark to mimic systems characteristics and effect of different sources of uncertainty. μ-synthesis is a robust control method which seeks a controller that minimizes the robust H-infinity performance of the closed-loop system through D-K iteration. The D-K iteration is not guaranteed to converge to a global, or even local minimum. Hence this paper proposes the enhancement of controller design by applying gazelle optimization technique to shape the fictitious output by determining the parameters of the performance weighting matrix. The incorporation of optimization with controller design allows avoiding getting unnecessarily conservative system at the expense of performance. The developed control system is simulated using Matlab R2023b for different scenarios of system uncertainty. The results show that the requirements of robustness and performance can be balanced through the right choice of cost function. The robust performance measure obtained is 0.6432 which leads to good response for both stabilization and tracking in the presence of uncertainty. The results also show that even the baseline μ-synthesis design achieves higher robust stability margin about 2.818, the proposed optimized method stabilizes the system with overshoot been reduced by 67.65% and steady state error reduced by 5.69% without sacrificing robustness.

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Section: Introductionmentioning

confidence: 99%

Balancing of Robustness and Performance for Triple Inverted Pendulum Using μ-Synthesis and Gazelle Optimization

Shafeek,

Ali

2024

JESA

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“…Motion Control of Triple Links Inverted Pendulum in Two Wheel System Using Type-2 Fuzzy Logic Interval Control Based on Particle Swarm Optimization was investigated by Masrom. A motion control of a three-link inverted pendulum on a two-wheeled system, through Interval Type-2 Fuzzy logic Control based on Particle Swarm Optimization [27]. The multilevel LQ and fieldoriented control of a mobile inverse pendulum (Segway) with a permanent magnet synchronous machine were investigated by Schiffer.…”

Section: Introductionmentioning

confidence: 99%

Synchronizing of Stabilizing Platform Mounted on a Two-Wheeled Robot

Islam¹,

Hossain²,

Banik³

2021

jrc

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This paper represents the designing, building, and testing of a self-stabilizing platform mounted on a selfbalancing robot. For the self-stabilizing platform, a servo motor is used and for the self-balancing robot, two dc motors are used with encoder, inertial measurement unit, motor driver, and Arduino UNO microcontroller board. A PID controller is used to control the balancing of the system. The PID controller gains (Kp, Ki, and Kd) were evaluated experimentally. The value of the tilted angle from IMU was fed to the PID controller to control the actuated motors for balancing the system. For the self-stabilizing control part, whenever the robot tilted, it maintained the horizontal position by rotating that much in the opposite direction.

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Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system

Nasir,

Ghani,

Nasir

et al. 2024

Journal of Low Frequency Noise, Vibration and Active Control

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Two-wheeled wheelchairs have been used as alternatives for the elderly and disabled people to perform physical activities due to their restriction of movement. Significant challenges posed by two-wheeled wheelchairs control due to their inherent instability, resembling that inverted pendulum system. This research addresses these challenges by developing a dynamic non-linear model and stability control using computational algorithms. A neural network-based Nonlinear Autoregressive model with Exogenous Inputs (NARX) was developed, capturing and behaving similar to the complex dynamics of the wheelchair system with the identification on the experimental input–output data. Ensuring stable and responsive control, design of optimized PD-type and PID-type fuzzy logic controllers using Particle Swarm Optimization (PSO) were established and were tested under a simulation environment. The performance was evaluated across various metrics, including Integral Squared Error (ISE), Integral Absolute Error (IAE), Mean Squared (MSE), and Integral Time Absolute Error (ITAE). The result demonstrates that the PSO Optimized PID-type fuzzy logic controller with scaling factor from MSE index performance come out as best overall, significantly outperforms PD-type fuzzy logic controller, reducing its settling time by 12.5% to 35 s, minimizing overshoot to 0.81°, and achieving a negligible steady-state error of 0.046%. These results highlight the significant of integrating fuzzy logic control and PSO to the neural network model in enhancing the stability and performance of two-wheeled wheelchair systems, offering user safety and comfort.

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Motion Control of Triple Links Inverted Pendulum on Two-Wheeled System Using Interval Type-2 Fuzzy Logic Control Base on Particle Swarm Optimization

Cited by 3 publications

References 13 publications

Balancing of Robustness and Performance for Triple Inverted Pendulum Using μ-Synthesis and Gazelle Optimization

Balancing of Robustness and Performance for Triple Inverted Pendulum Using μ-Synthesis and Gazelle Optimization

Synchronizing of Stabilizing Platform Mounted on a Two-Wheeled Robot

Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system

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