Heuristic Global Optimization of an Adaptive Fuzzy Controller for the Inverted Pendulum System: Experimental Comparison

Llama, Miguel A.; Flores, Alejandro; Garcia-Hernandez, Ramon; Santibáñez, Víctor

doi:10.3390/app10186158

Cited by 15 publications

(9 citation statements)

References 27 publications

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“…The state-feedback controller was designed first for the nonlinear model then it was updated for the Real-Time implementation. In fuzzy logic, different optimization algorithms are used to find the optimal input setting for a reverse pendulum: In [8], an adaptive fuzzy controller is proposed to solve the trajectory tracking problem of the inverted pendulum on a cart system. The designed algorithm is featured by not using any knowledge of the dynamic model and incorporating a full-state feedback.…”

Section: Related Workmentioning

confidence: 99%

Provide A Method Based on Genetic Algorithm to Optimize the Fuzzy Logic Controller for the Inverted Pendulum

Alimoradpour

Rafie

Ahmadzadeh

2021

Preprint

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One of the classic systems in dynamics and control is the inverted pendulum, which is known as one of the topics in control engineering due to its properties such as nonlinearity and inherent instability. Different approaches are available to facilitate and automate the design of fuzzy control rules and their associated membership functions. Recently, different approaches have been developed to find the optimal fuzzy rule base system using genetic algorithm. The purpose of the proposed method is to set fuzzy rules and their membership function and the length of the learning process based on the use of a genetic algorithm. The results of the proposed method show that applying the integration of a genetic algorithm along with Mamdani fuzzy system can provide a suitable fuzzy controller to solve the problem of inverse pendulum control. The proposed method shows higher equilibrium speed and equilibrium quality compared to static fuzzy controllers without optimization. Using a fuzzy system in a dynamic inverted pendulum environment has better results compared to definite systems, and in addition, the optimization of the control parameters increases the quality of this model even beyond the simple case.

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Section: Related Workmentioning

confidence: 99%

Provide A Method Based on Genetic Algorithm to Optimize the Fuzzy Logic Controller for the Inverted Pendulum

Alimoradpour

Rafie

Ahmadzadeh

2021

Preprint

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“…Then, the applied input vibrations asymptotically stabilize the averaged system given in (15) and linearized pendulum system in water given in (14). Hence, the lower stability border of an inverted pendulum system in water is given by the following inequality:…”

Section: Parametric Excitation Control Of Inverted Pendulum In Watermentioning

confidence: 99%

“…For example, the design of an active stabilizing system for a single-track vehicle system was studied [12], and an intelligent control and balancing technique for a robotics system has been formulated [13]. A fuzzy controller has been suggested to solve the trajectory tracking problem of the inverted pendulum attached to a cart system [14], while a particle swarm optimization-based neural network controller has been designed for solving a real world unstable control challenge [15]. The mechanical systems mentioned above have been developed based on the dynamic design of pendulum systems in an open environment like air or vacuum.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Response of an Inverted Pendulum System in Water under Parametric Excitations for Energy Harvesting: A Conceptual Approach

et al. 2020

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In this paper, we have investigated the dynamic response, vibration control technique, and upright stability of an inverted pendulum system in an underwater environment in view point of a conceptual future wave energy harvesting system. The pendulum system is subjected to a parametrically excited input (used as a water wave) at its pivot point in the vertical direction for stabilization purposes. For the first time, a mathematical model for investigating the underwater dynamic response of an inverted pendulum system has been developed, considering the effect of hydrodynamic forces (like the drag force and the buoyancy force) acting on the system. The mathematical model of the system has been derived by applying the standard Lagrange equation. To obtain the approximate solution of the system, the averaging technique has been utilized. An open loop parametric excitation technique has been applied to stabilize the pendulum system at its upright unstable equilibrium position. Both (like the lower and the upper) stability borders have been shown for the responses of both pendulum systems in vacuum and water (viscously damped). Furthermore, stability regions for both cases are clearly drawn and analyzed. The results are illustrated through numerical simulations. Numerical simulation results concluded that: (i) The application of the parametric excitation control method in this article successfully stabilizes the newly developed system model in an underwater environment, (ii) there is a significant increase in the excitation amplitude in the stability region for the system in water versus in vacuum, and (iii) the stability region for the system in vacuum is wider than that in water.

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“…Urrea et al [12] proposed a variable universe fuzzy adaptive control method, which solves the problem of inaccurate control in traditional fuzzy control. Llama et al [13] realized the control of nonlinear systems such as four-stage inverted pendulum by using the variable universe fuzzy method. Zhang et al [14] used the variable universe method to realize the vehicle lateral autonomous control.…”

Section: Introductionmentioning

confidence: 99%

Motion Trajectory Control System for Production Line Robots Based on Variable Domain Fuzzy Control

Pan

2022

Advances in Multimedia

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Mechatronics production line is widely used in the production and operation of all walks of life, which greatly reduces the amount of labor of employees, improves the production level of enterprises, and creates great social and economic benefits for enterprises. The traditional manipulator system has modeling uncertainty and is vulnerable to external interference. In this paper, a compound control scheme is designed by combining the torque controller and fuzzy compensator, which effectively improves the system's response speed and greatly reduces the steady-state tracking error of the system. At the same time, the tracking process of the scheme is stable and flexible, and the chattering is minimal, which effectively improves the trajectory tracking performance of the system. Experiments show that the algorithm effectively solves the contradiction between computational complexity and control accuracy, improves the system's response speed, and reduces the system's steady-state tracking error.

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Heuristic Global Optimization of an Adaptive Fuzzy Controller for the Inverted Pendulum System: Experimental Comparison

Cited by 15 publications

References 27 publications

Provide A Method Based on Genetic Algorithm to Optimize the Fuzzy Logic Controller for the Inverted Pendulum

Provide A Method Based on Genetic Algorithm to Optimize the Fuzzy Logic Controller for the Inverted Pendulum

Dynamic Response of an Inverted Pendulum System in Water under Parametric Excitations for Energy Harvesting: A Conceptual Approach

Motion Trajectory Control System for Production Line Robots Based on Variable Domain Fuzzy Control

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