A Robust Control via a Fuzzy System with PID for the ROV

Dong, Jie; Duan, Xingguang

doi:10.3390/s23020821

Cited by 11 publications

(4 citation statements)

References 41 publications

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“…Fuzzy rules are a powerful tool for modeling complex systems and making decisions. They are especially useful when the relationships between variables are not fully understood or when the data is noisy and uncertain, showing a high level of flexibility (Velo et al, 2023), reliability (Dong & Duan, 2023), and easy interpretation (Vasilakakis & Iakovidis, 2023).…”

Section: Fuzzy Logicmentioning

confidence: 99%

Burnout: A Pervasive Challenge Threatening Workplace Well-Being and Organizational Success

Bouhsaien,

Azmani

2024

J. Professional Business Review

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Objective: This study aims to tackle the increasing prevalence of employee burnout by introducing a novel hybrid methodology employing Bayesian networks and fuzzy logic. This approach seeks to identify and address burnout risks comprehensively. Theoretical Framework: Drawing from burnout theories alongside Bayesian networks and fuzzy logic, this research establishes a robust foundation for understanding burnout complexities and evaluating the efficacy of the proposed hybrid approach. Method: The methodology encompasses a model development phase utilizing OpenMarkov and FisPro to integrate Bayesian networks and fuzzy logic. Data collection involved a multifaceted approach including surveys, expert interviews, and a thorough review of literature focusing on workload, work environment, psychology, and other pertinent factors influencing burnout. Results and Discussion: Findings indicate that burnout tends to manifest at lower levels in scenarios characterized by weak communication, high workload, and low obstacles, while it escalates in situations marked by weak communication, occasional workload spikes, and moderate obstacles, among other contributing factors. These results are analyzed within the context of the theoretical framework, emphasizing their implications for individual well-being and organizational success. Research Implications: This study provides actionable insights for companies, particularly human resources managers, to bolster employee psychological support systems and advance organizational objectives. Proactively addressing burnout risks can enhance both employee well-being and overall organizational performance. Originality/Value: By proposing a hybrid methodology that merges Bayesian networks and fuzzy logic to comprehensively tackle burnout risks, this research contributes to the existing literature. The innovative methodology and practical implications underscore the significance and applicability of this study for organizations striving to mitigate burnout within their workforce.

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Section: Fuzzy Logicmentioning

confidence: 99%

Burnout: A Pervasive Challenge Threatening Workplace Well-Being and Organizational Success

Bouhsaien,

Azmani

2024

J. Professional Business Review

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“…Therefore, a method of adjusting the length of the DAVAR window based on the adaptive PID principle is proposed. The length of the truncation window is adjusted adaptively to achieve better tracking ability and ideal variance confidence [25,26].…”

Section: Dynamic Allan Variance Based On Adaptive Pid Principle 41 Pi...mentioning

confidence: 99%

“…The premise of the PID-DAVAR adaptive algorithm is to input the measured MEMS gyroscope original signal, sampling time T, set the initial window length L 0 , and the initial deviation index ε 0 = 0. The deviation index ε k is calculated by Equation (26). The deviation index ε k can be regarded as e(k) in Equation (25).…”

Section: Pid-davar Adaptive Algorithmmentioning

confidence: 99%

Adaptive Dynamic Analysis of MEMS Gyroscope Random Noise Based on PID-DAVAR

Zhang

et al. 2023

Micromachines

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As a MEMS gyroscope is susceptible to environmental interference, its performance is degraded due to random noise. Accurate and rapid analysis of random noise of MEMS gyroscope is of great significance to improve the gyroscope’s performance. A PID-DAVAR adaptive algorithm is designed by combining the PID principle with DAVAR. It can adaptively adjust the length of the truncation window according to the dynamic characteristics of the gyroscope’s output signal. When the output signal fluctuates drastically, the length of the truncation window becomes smaller, and the mutation characteristics of the intercepted signal are analyzed detailed and thoroughly. When the output signal fluctuates steadily, the length of the truncation window becomes larger, and the intercepted signals are analyzed swiftly and roughly. The variable length of the truncation window ensures the confidence of the variance and shortens the data processing time without losing the signal characteristics. Experimental and simulation results show that the PID-DAVAR adaptive algorithm can shorten the data processing time by 50%. The tracking error of the noise coefficients of angular random walk, bias instability, and rate random walk is about 10% on average, and the minimum error is about 4%. It can accurately and promptly present the dynamic characteristics of the MEMS gyroscope’s random noise. The PID-DAVAR adaptive algorithm not only satisfies the requirement of variance confidence but also has a good signal-tracking ability.

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“…The industry uses proportional integral derivative (PID) control extensively, which improves the system's transient and steady-state behavior [6]- [8]. To accomplish the conditions as per the anticipated setpoint, this control system processes computations based on the control variables Kp, Ki, and Kd.…”

Section: Introductionmentioning

confidence: 99%

Controlling parameters proportional integral derivative of DC motor using a gradient-based optimizer

Aribowo,

Rahmadian,

Widyartono

et al. 2024

IJPEDS

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In this paper, a gradient-based optimizer (GBO) algorithm is presented to optimize the parameters of a proportional integral derivative (PID) controller in DC motor control. The GBO algorithm which mathematically models and mimics is inspired by the gradient-based Newton method. It was developed to address various optimization issues. To determine the performance of the proposed method, a comparison method with the ant colony optimization (ACO) method. It was compared using the integral of time multiplied absolute error (ITAE). They are most popularly used in the literature. From the test results, the proposed method is promising and has better effectiveness. The proposed method, namely GBO-PID, shows the best performance.

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A Robust Control via a Fuzzy System with PID for the ROV

Cited by 11 publications

References 41 publications

Burnout: A Pervasive Challenge Threatening Workplace Well-Being and Organizational Success

Burnout: A Pervasive Challenge Threatening Workplace Well-Being and Organizational Success

Adaptive Dynamic Analysis of MEMS Gyroscope Random Noise Based on PID-DAVAR

Controlling parameters proportional integral derivative of DC motor using a gradient-based optimizer

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