Fuzzy gain scheduling PID control of a hybrid robot based on dynamic characteristics

Han, Jiale; Shan, Xianlei; Liu, Haitao; Xiao, Juliang; Huang, Tian

doi:10.1016/j.mechmachtheory.2023.105283

Cited by 29 publications

(18 citation statements)

References 35 publications

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“…Current coils or permanent magnets can generate a stator field. When a fixed field current pours in the field coil, the motor torque (τ_m) shown as (1).…”

Section: Methods 21 DC Motormentioning

confidence: 99%

See 1 more Smart Citation

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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“…Current coils or permanent magnets can generate a stator field. When a fixed field current pours in the field coil, the motor torque (τ_m) shown as (1).…”

Section: Methods 21 DC Motormentioning

confidence: 99%

“…There are various sorts of control actions in a control system, including proportional, integral, and derivative control actions [1]- [4]. There are benefits to each of these control measures.…”

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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show abstract

“…Because of its simplicity in structure and the relatively easy tuning of parameters, the Proportional Integral Derivative (PID) controller is applied in different control system [2]. Fuzzy logic was used to schedul of the PID controller to control the hybrid robot manipulator [3]. Fuzzy type 2 had been proposed for the control of the 2dof robotic manipulator with Grey wolf optimization used for tuning the parameters [4].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Robust Tracking Control of Robotic Manipulator based on SMC and Fuzzy Control Strategy

Mary,

Al-Talabi,

Kara

et al. 2024

alkej

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In recent years, robotic systems have been widely used in different applications, and this has motivated researchers to develop different control methods. A model-free, intelligent, robust control method for a nonlinear robotic manipulator system is proposed in this work. This paper presents a novel solution for the major drawbacks of the sliding mode control scheme, which are chattering. Prior knowledge is needed about the dynamic model of the controlled system and the upper bound of uncertainty. In this paper, a fuzzy-like PD controller with SMC (FLPDSM) is proposed. The fuzzy-like PD controller was designed according to fuzzy rules and membership functions based on the nominal model of the robot manipulator. A robust control term was added to the control signal to compensate for the system uncertainty, and external disturbances are compensated by adding an auxiliary robust term to the SMC control law. Two methods for designing robust control terms are proposed. The first proposed method assumes that the upper bound of system uncertainty is known although it cannot be exactly determined due to external disturbances and uncertainty. Hence, a second method was proposed that assumes this bound to be unknown, and an adaptive gain based on Lyapunov theory was used to derive the adaptation law. The Lyapunov second method was used to ensure the stability of the closed loop system. Performance tests on the proposed methods were implemented through simulation studies for the two-link robotic manipulator, and the test results were compared with the standard SMC to verify the effectiveness of the proposed method. A good trajectory tracking with a high robustness against parameter variations and external disturbances was observed under the presented control scheme.

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“…With the development of technology, some new parameter tuning methods continue to emerge. The Fuzzy PID control algorithm uses fuzzy logic to optimize and tune PID parameters in real time according to certain fuzzy rules [13][14][15][16]. However, this method relies on operators' experience to establish fuzzy rules, making it unsuitable for systems that require frequent changes in conditions.…”

Section: Introductionmentioning

confidence: 99%

A Temperature Control Method of Lysozyme Fermentation Based on LRWOA-LSTM-PID

Ding,

Li,

Zhou

et al. 2024

Processes

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In order to overcome the difficulty of parameter tuning caused by the large lag and time-varying nonlinearity of the tank for lysozyme fermentation, a temperature control method based on LRWOA-LSTM-PID is proposed in this paper. Firstly, according to the intrinsic mechanism of the fermenter, a temperature mechanism model based on a dynamic equation is designed, which can better reflect the temperature changes in the fermenter. Secondly, a Proportional Integral Derivative (PID) parameter tuning method based on a Long-Short Term Memory Network (LSTM) is proposed, which takes advantage of the ability of LSTM to learn time sequence information and obtains the variation trend between error sequences under continuous time sampling, thereby adjusting network weights more reasonably and accelerating PID parameter tuning. Finally, a Whale Optimization Algorithm (WOA) based on the Lévy flight and random walk strategy (LRWOA) is proposed for the initialization of LSTM parameters; this algorithm has excellent optimization capabilities and overcomes the problem of LSTM falling into local optimal solutions prematurely during parameter randomization. The results show that the method proposed in this paper can achieve rapid tuning of PID parameters, thereby improving the convergence speed of the system and reducing system overshoot.

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Fuzzy gain scheduling PID control of a hybrid robot based on dynamic characteristics

Cited by 29 publications

References 35 publications

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

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

Adaptive Robust Tracking Control of Robotic Manipulator based on SMC and Fuzzy Control Strategy

A Temperature Control Method of Lysozyme Fermentation Based on LRWOA-LSTM-PID

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