Robust yaw control of autonomous underwater vehicle based on fractional-order PID controller

Liu, Lu; Zhang, Lichuan; Pan, Guang; Zhang, Shuo

doi:10.1016/j.oceaneng.2022.111493

Cited by 68 publications

(30 citation statements)

References 19 publications

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“…The FOPID controller is a development of the PID controller model that has been around for a long time and is widely applied in industrial control systems. FOPID controls drive correction when errors between reference points and process variables occur [26]- [29]. This is done by calculating and responding with corrections that can adjust the process accordingly.…”

Section: Fractional Order Pidmentioning

confidence: 99%

Optimal tuning fractional order PID based on marine predator algorithm for DC motor

Aribowo

Suprianto

Rahmadian

et al. 2023

IJPEDS

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DC motors are a popular topic because they are widely applied in various electronic equipment. So, this requires a control that is fast and reliable. The development of optimized control methods is growing rapidly with the discovery of several new methods. Marine predator algorithm (MPA) is an optimization method based on marine life between living things. This article discusses the application of the MPA method for optimizing fractional order PID (FOPID) control on DC motors. The implementation of the FOPID controller is also difficult because the fractional calculus operators of the FOPID controller cannot be directly implemented in numerical calculations. The method proposed in this article is the FOPID-MPA method. To get a performance test of the proposed method, this study uses several comparison methods, namely the seagull optimization algorithm (ASO), chimp optimization algorithm (ChOA), and sine tree seed algorithm (STSA). This study also uses a variation of the reference speed to get the performance of the proposed method. From the experiment it is known that the FOPID-MPA method gives the best performance. The FOPID-MPA method has an overshoot value of 4.34% compared to the PID-MPA method in case study 1 and has an integrated of time-weighted-squared-error (ITSE) value of 7.44% better than the PID-MPA method in case study 2.

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Section: Fractional Order Pidmentioning

confidence: 99%

Optimal tuning fractional order PID based on marine predator algorithm for DC motor

Aribowo

Suprianto

Rahmadian

et al. 2023

IJPEDS

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show abstract

“…A fractional derivative is a generalization of the integer-order derivatives, which have been widely applied in different fields, such as dynamics, engineering, computer science, etc. [22][23][24][25][26][27][28]. Fractional derivative damping is usually utilized to describe the viscoelastic damping model.…”

Section: Fractional Derivativementioning

confidence: 99%

Stationary Response of a Kind of Nonlinear Stochastic Systems with Variable Mass and Fractional Derivative Damping

2022

Self Cite

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Viscoelasticity and variable mass are common phenomena in Micro-Electro-Mechanical Systems (MEMS), and could be described by a fractional derivative damping and a stochastic process, respectively. To study the dynamic influence cased by the viscoelasticity and variable mass, stationary response of a kind of nonlinear stochastic systems with stochastic variable-mass and fractional derivative, damping is investigated in this paper. Firstly, an approximately equivalent system of the studied nonlinear stochastic system is presented according to the Taylor expansion technique. Then, based on stochastic averaging of energy envelope, the corresponding Fokker–Plank–Kolmogorov (FPK) equation is deduced, which gives an approximated analytical solution of stationary response. Finally, a nonlinear oscillator with variable mass and fractional derivative damping is proposed in numerical simulations. The approximated analytical solution is compared with Monte Carlo numerical solution, which could verify the effectiveness of the obtained results.

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“…First, the motion model of a single AUV was established. Take the eastward position x, northward position y, and heading angle ψ of the AUV as the state vector of the system and neglect the disturbance factors such as ocean currents to establish the following kinematic equations of the AUV [24][25][26].…”

Section: Mathematical Modelmentioning

confidence: 99%

Multi-AUV Cooperative Navigation Algorithm Based on Temporal Difference Method

Ren

Zhang

Liu

et al. 2022

JMSE

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To reduce the cooperative positioning error and improve the navigation accuracy, a single master–slave AUV cooperative navigation method is proposed in this paper, which mainly focuses on planning the optimal path of the master AUV by the time difference (TD) method, under the premise that the path of the slave AUV has been planned. First, the model of multi-AUV cooperative navigation is established, and the observable problem of the system is analyzed. Second, for the single master–slave AUV cooperative navigation system, a Markov decision process (MDP)-based multi-AUV cooperative navigation model is established, and the master AUV path planning method is designed based on the TD method. Finally, the extended Kalman filter (EKF) and unscented Kalman filter (UKF) nonlinear filtering algorithms are applied to simulate and verify the algorithm that is proposed in this paper. The results show that the theoretical positioning error of the slave AUV can be controlled to about 3.2m by planning the path of the master AUV using the TD method. This method can not only reduce the observation error and positioning error of the slave AUV during the whole cooperative navigation process, but also keep the relative measurement distance between the master AUV and the slave AUV within an appropriate range.

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Robust yaw control of autonomous underwater vehicle based on fractional-order PID controller

Cited by 68 publications

References 19 publications

Optimal tuning fractional order PID based on marine predator algorithm for DC motor

Optimal tuning fractional order PID based on marine predator algorithm for DC motor

Stationary Response of a Kind of Nonlinear Stochastic Systems with Variable Mass and Fractional Derivative Damping

Multi-AUV Cooperative Navigation Algorithm Based on Temporal Difference Method

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