Fuzzy logic and gradient descent-based optimal adaptive robust controller with inverted pendulum verification

Lakmesari, S. Hadipour; Mahmoodabadi, Mohammad Javad; Ibrahim, M. Yousef

doi:10.1016/j.chaos.2021.111257

Cited by 17 publications

(7 citation statements)

References 31 publications

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“…To minimize the Hamiltonian error

, it is necessary to maintain the derivative of

. Therefore, the critic weight adjustment law is derived by employing the normalization term

and applying the gradient descent method with respect to

[ 49 ].…”

Section: Critic Network For Approximationmentioning

confidence: 99%

Reinforcement Learning-Based Decentralized Safety Control for Constrained Interconnected Nonlinear Safety-Critical Systems

Qin

Zhang

et al. 2023

Entropy

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This paper addresses the problem of decentralized safety control (DSC) of constrained interconnected nonlinear safety-critical systems under reinforcement learning strategies, where asymmetric input constraints and security constraints are considered. To begin with, improved performance functions associated with the actuator estimates for each auxiliary subsystem are constructed. Then, the decentralized control problem with security constraints and asymmetric input constraints is transformed into an equivalent decentralized control problem with asymmetric input constraints using the barrier function. This approach ensures that safety-critical systems operate and learn optimal DSC policies within their safe global domains. Then, the optimal control strategy is shown to ensure that the entire system is uniformly ultimately bounded (UUB). In addition, all signals in the closed-loop auxiliary subsystem, based on Lyapunov theory, are uniformly ultimately bounded, and the effectiveness of the designed method is verified by practical simulation.

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“…To minimize the Hamiltonian error

, it is necessary to maintain the derivative of

. Therefore, the critic weight adjustment law is derived by employing the normalization term

and applying the gradient descent method with respect to

[ 49 ].…”

Section: Critic Network For Approximationmentioning

confidence: 99%

Reinforcement Learning-Based Decentralized Safety Control for Constrained Interconnected Nonlinear Safety-Critical Systems

Qin

Zhang

et al. 2023

Entropy

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show abstract

“…PID controllers whose parameters are constantly updated can be used for systems that need a different PID controller due to the change in system characteristics [32]. The control performance can be increased by manipulating the PID controller output signal u with a fuzzy logic controller, which reduces the control performance due to external disturbances and the time-dependent change of the system dynamic response [33].…”

Section: Blast Furnace Gas Cleaning Tank Level Control Systemmentioning

confidence: 99%

Level Control of Blast Furnace Gas Cleaning Tank System with Fuzzy Based Gain Regulation for Model Reference Adaptive Controller

2022

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Iron making processes and automation systems are mostly controlled by logical rules and PID controllers. The dynamic behavior of these processes varies due to factors such as raw materials, outdoor conditions, and equipment aging. Changes in system dynamics necessitate re-determination of PID controller parameters. Model reference adaptive controllers (MRACs) are used in many industrial application areas with their adaptability to variable conditions. In this study, an MRAC is applied in the gas cleaning tank system level control problem in the blast furnace facility, which is at the center of the iron making processes. In addition, fuzzy based gain regulation is proposed to improve MRAC performance. MRAC and PID controller system control results are observed and compared. The fast response and adaptation performance of the proposed fuzzy MRAC approach along with external disturbance effects are analyzed. Fuzzy based gain regulation MRAC performances show better performance especially in level change as well as disturbance effect.

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“…An adaptive optimal fuzzy controller based on feedback linearization and sliding mode control was proposed in ref. [11] for cartpole systems. Fuzzy logic system and gradient descent were combined to tune the parameters and a multi-object optimization algorithm was used to adjust sliding mode control gain.…”

Section: Introductionmentioning

confidence: 99%

Design and stability analysis of semi-implicit cascaded proportional-derivative controller for underactuated cart-pole inverted pendulum system

Lei,

Li,

Zhu

2023

Robotica

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This article proposes a control method for underactuated cartpole systems using semi-implicit cascaded proportional-derivative (PD) controller. The proposed controller is composed of two conventional PD controllers, which stabilizes the pole and the cart second-order dynamics respectively. The first PD controller is realized by transforming the pole dynamics into a virtual PD controller, with the coupling term exploited as the internal tracking target for the cart dynamics. Then, the second PD controller manipulates the cart dynamics to track that internal target. The solution to the internal tracking target relies on an equation set and features a semi-implicit process, which exploits the internal dynamics of the system. Besides, the design of second PD controller relies on the parameters of the first PD controller in a cascaded manner. A stability analysis approach based on Jacobian matrix is proposed and implemented for this fourth-order system. The proposed method is simple in design and intuitive to comprehend. The simulation results illustrate the superiority of proposed method compared with conventional double-loop PD controller in terms of convergence, with the theoretical conclusion of at least locally asymptotic stability.

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Fuzzy logic and gradient descent-based optimal adaptive robust controller with inverted pendulum verification

Cited by 17 publications

References 31 publications

Reinforcement Learning-Based Decentralized Safety Control for Constrained Interconnected Nonlinear Safety-Critical Systems

Reinforcement Learning-Based Decentralized Safety Control for Constrained Interconnected Nonlinear Safety-Critical Systems

Level Control of Blast Furnace Gas Cleaning Tank System with Fuzzy Based Gain Regulation for Model Reference Adaptive Controller

Design and stability analysis of semi-implicit cascaded proportional-derivative controller for underactuated cart-pole inverted pendulum system

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