Stabilization of Three Links Inverted Pendulum with Cart Based on Genetic LQR Approach

Abdullah, Abdullah Ibrahim; Alnema, Yazen Hudhaifa Shakir; Thanoon, Mohammad A.

doi:10.18280/jesa.550113

Cited by 5 publications

(3 citation statements)

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“…The fitness function (function of evaluation): Defined to be proportional to the ability or utility of the chromosome, to evaluate and compare every solution to the other one. The fitness function must be developed with respect of several criteria, by taking into account the satisfying of the constraints existing in the problem [19,20].…”

Section: The Ga Methodsmentioning

confidence: 99%

An Optimal GA-Based Backstepping Control Scheme for a MIMO Nonlinear System

Saidi¹,

Boumédiène²,

Boubekeur³

2023

JESA

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In the presence of external disturbances, a backstepping control scheme based a genetic algorithm (GA) is built with the objective of tracking a desired trajectory of robot manipulators. The nonlinear-coupled higher order dynamic model of an n-link robot manipulator is first briefly presented. Then, a traditional backstepping control system (BSC) creates a two-link robotic manipulator position tracking control. Furthermore, a mix of nonlinear control and artificial intelligence is suggested for manipulator robot control. To determine the optimal control parameters, the backstepping controller is combined with the genetic algorithm, a metaheuristics-based optimization technique. The effectiveness of the suggested optimal control strategy based on backstepping approach and GA in trajectory tracking problems, such as a good angle tracking and a good disturbance rejection capability, is demonstrated by numerical simulations using the dynamic model of a two-link planar rigid robot manipulator.

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Section: The Ga Methodsmentioning

confidence: 99%

An Optimal GA-Based Backstepping Control Scheme for a MIMO Nonlinear System

Saidi¹,

Boumédiène²,

Boubekeur³

2023

JESA

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“…Erkol [22] presented a fractional order PID controller for the position control of a two wheeled inverted pendulum and compared the performance of artificial bee colony, particle swarm optimization, grey wolf optimizer, and cuckoo search algorithm in finding the best parameter of this controller. Abdullah et al [23] employed Linear Quadratic Regulator (LQR) to stabilize a Three Links Inverted Pendulum with Cart and parameters was determined with the help of Genetic Algorithm (GA).…”

Section: Related Workmentioning

confidence: 99%

Intelligent and Robust Controller Tuned with WOA: Applied for the Inverted Pendulum

Mourad¹,

Zennir²,

Tolba³

2022

JESA

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Inverted pendulum is a well-known problem in the control theory because several systems such as robot balancing, Segway, hover board riding and operation of a rocket propeller are inherently based on Inverted Pendulum, furthermore it possesses a height non-linear and unstable dynamics. The main objective of our study is to introduce a comparative analysis of fuzzy logic (FLC), radial basis function neural network (RBF) and integral sliding mode control (ISMC) tuned with whale optimizer algorithm (WOA) for the control of the angle position and velocity of the inverted pendulum system. The implemented controller schemas can adequately reflect and approximate a certain type of uncertainties, nevertheless their parameters should be fine-tuned in order to get height and efficient performance, therefore all the antecedents and consequences of those controllers were tuned with WOA. This later provide height accuracy and fast convergence with height dimensional cost function. Comparative results shows that ISMC-WOA outperforms other techniques in term of settling time and overshoot.

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“…Different studies have been made regarding the control of triple inverted pendulum system. The researches [2][3][4][5][6] used adaptive optimal control, fuzzy logic, Linear Quadratic Regulator (LQR), LQR with Genetic Algorithm, fuzzy LQR optimized by Particle Swarm Optimization (PSO), and interval type-2 fuzzy logic control (IT2FLC) with PSO methods but applied it to the linearized model which doesn't show the real nonlinear system response.…”

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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Stabilization of Three Links Inverted Pendulum with Cart Based on Genetic LQR Approach

Cited by 5 publications

References 0 publications

An Optimal GA-Based Backstepping Control Scheme for a MIMO Nonlinear System

An Optimal GA-Based Backstepping Control Scheme for a MIMO Nonlinear System

Intelligent and Robust Controller Tuned with WOA: Applied for the Inverted Pendulum

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

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