Design of a Fuzzy Logic Controller for the Double Pendulum Inverted on a Cart

Maraslidis, George S.; Kottas, Theodore; Tsipouras, Markos G.; Fragulis, George F.

doi:10.3390/info13080379

Cited by 13 publications

(10 citation statements)

References 25 publications

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“…Double inverted pendulum is a modification of the inverted pendulum, which adds one more pendulum that is assembled in connection with each other and mounted on a cart. Figure 1 shows the double inverted pendulum [4]. The following is a table of parameters for the double inverted pendulum system [3]:…”

Section: Model Of Double Inverted Pendulum Systemmentioning

confidence: 99%

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LQR and Fuzzy-PID Control Design on Double Inverted Pendulum

Damayanti

2024

CAUCHY

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Double inverted pendulum is a non-linear and unstable system. Double inverted pendulum can be stabilized in the upright position by providing control to the system. In this research we compare two types of controllers namely Linear Quadratic Regulator (LQR) and Fuzzy-PID. The objective is to determine the control strategy that provides better performance on the position of the cart and pendulum angle. We modelled the system which is then linearized and given control. From the simulation results, it is proven that LQR and Fuzzy-PID controllers have been successfully designed to stabilize the double inverted pendulum. However, when given a disturbance in the form of noise step, the LQR controller has not been able to achieve the desired reference for up to 20 seconds. In another hand, the Fuzzy-PID controller is able to achieve the desired reference after 8 seconds. Therefore, it can be concluded that the Fuzzy-PID controller when applied to the Double Inverted pendulum system has better performance than the LQR controller.

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Section: Model Of Double Inverted Pendulum Systemmentioning

confidence: 99%

“…If the oscillating cart is completely upright and the frequency is high, the double pendulum can be stabilized. Without an appropriate force on the double pendulum, the pendulum will fall over [4].…”

Section: Introductionmentioning

confidence: 99%

LQR and Fuzzy-PID Control Design on Double Inverted Pendulum

Damayanti

2024

CAUCHY

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“…Artificial intelligence technologies have the potential to greatly improve the lives of people who are deaf or hard of hearing by removing barriers to communication. In light of recent developments in sensing technologies and AI algorithms, a wide range of applications have been created to meet the demands of deaf and hearing-impaired individuals [64][65][66].…”

Section: Related Work In Sign Language Recognition Using Iotmentioning

confidence: 99%

A Survey of Advancements in Real-Time Sign Language Translators: Integration with IoT Technology

2023

Self Cite

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Real-time sign language translation systems are of paramount importance in enabling communication for deaf and hard-of-hearing individuals. This population relies on various communication methods, including sign languages and visual techniques, to interact with others. While assistive technologies, such as hearing aids and captioning, have improved their communication capabilities, a significant communication gap still exists between sign language users and non-users. In order to bridge this gap, numerous sign language translation systems have been developed, encompassing sign language recognition and gesture-based controls. Our research aimed to analyze the advancements in real-time sign language translators developed over the past five years and their integration with IoT technology. By closely examining these technologies, we aimed to attain a deeper comprehension of their practical applications and evolution in the domain of sign language translation. We analyzed the current literature, technical reports, and conference papers on real-time sign language translation systems. Our results offer insights into the current state of the art in real-time sign language translation systems and their integration with IoT technology. We also provide a deep understanding of the recent developments in sign language translation technology and the potential for their fusion with Internet of Things technology to improve communication and promote inclusivity for the deaf and hard-of-hearing population.

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“…Below, we will briefly introduce one method to derive the solution for K. Suppose our goal is to design a state feedback controller that keeps the angle of the inverted pendulum near the target angle. According to the LQR theory [8,25], our control objective can be defined as minimizing the cost function J:…”

Section: Linear Modelmentioning

confidence: 99%

“…The system's dynamics are driven by gravity and the constraint force of the rod, resulting in various dynamic phenomena such as robotic motion, periodic motion, chaotic motion, and stability analysis. Due to its nonlinear nature, the inverted pendulum poses challenges for control and stabilization [7][8][9][10][11]. Recent studies have explored the decoupling control of nonlinear systems using Tikhonov regularization theory.…”

Section: Introductionmentioning

confidence: 99%

Tikhonov-Tuned Sliding Neural Network Decoupling Control for an Inverted Pendulum

Mon

2023

Electronics

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This paper introduces the concept of intelligent control using Tikhonov regularization for nonlinear coupled systems. This research is driven by the increasing demand for advanced control techniques and aims to explore the impact of Tikhonov regularization on these systems. The primary objective is to determine the optimal regularization term and its integration with other control methods to enhance intelligent control for nonlinear coupled systems. Tikhonov regularization is a technique employed to adjust neural network weights and prevent overfitting. Additionally, the incorporation of ReLU activation function in the neural network simplifies thearchitecture, avoiding issues like gradient explosion, and optimizes controller performance. Furthermore, sliding surfaces are designed to improve control system stability and robustness. The proposed Tikhonov-tuned sliding neural network (TSN) controller ensures both stability and superior system performance. The methodology emphasizes the importance of determining optimal neural network weights and regularization terms to prevent overfitting, facilitating accurate predictions in inverted pendulum control system applications. To assess the functionality and stability of TSN, this paper employs simulations and experimental implementations to control both the rotary inverted pendulum and the arm-driven inverted pendulum. The results indicate that the proposed TSN methodologies are effective and feasible.

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Design of a Fuzzy Logic Controller for the Double Pendulum Inverted on a Cart

Cited by 13 publications

References 25 publications

LQR and Fuzzy-PID Control Design on Double Inverted Pendulum

LQR and Fuzzy-PID Control Design on Double Inverted Pendulum

A Survey of Advancements in Real-Time Sign Language Translators: Integration with IoT Technology

Tikhonov-Tuned Sliding Neural Network Decoupling Control for an Inverted Pendulum

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