Fuzzy fractional-order PID control for two-wheeled self-balancing robots on inclined road surface

Zhang, Jiawen; Zhao, Tao; Guo, Bin; Dian, Songyi

doi:10.1080/21642583.2021.2001768

Cited by 9 publications

(2 citation statements)

References 22 publications

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“…PID control is widely used in various industrial and automation systems, including temperature control, speed control, position control, and more [10]. It is a simple yet effective control method, but for complex systems or applications that require more advanced control strategies, a combination or improvement of other control methods may be needed.…”

Section: Pid Control Principlementioning

confidence: 99%

Speed regulation of electric vehicle motor based on PID control

Zhu

2023

TNS

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Electric vehicles, as a new technological advancement in the automotive industry for addressing energy and environmental issues, have become a hot topic in both domestic and international car development. The electric vehicle generator, which plays a crucial role, is a key component of electric vehicles. The Alternating Current (AC) motor in electric vehicles is highly efficient and widely used in various fields. Therefore, studying AC motors holds significant theoretical and practical significance. This article first explains the car model and the principle of the electric motor, followed by an analysis of the ProportionalIntegralDerivative (PID) principle. Finally, through PID control, the simulation of the electric vehicle's speed is conducted to achieve better stability and economy. The experiments demonstrate that by improving the phase margin and stability of the lag compensator and feedback loop system, the driving comfort and practicality of electric vehicles can be effectively enhanced.

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Section: Pid Control Principlementioning

confidence: 99%

Speed regulation of electric vehicle motor based on PID control

Zhu

2023

TNS

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“…To address this issue, some scholars have started exploring data-driven control approaches. PID control is one of the earliest control methods and has been widely applied in industrial processes due to its advantages of simplicity and high reliability [21,22]. Moreover, the PID is also a typical data-driven control method.…”

Section: Introductionmentioning

confidence: 99%

A Novel Model-Free Adaptive Proportional–Integral–Derivative Control Method for Speed-Tracking Systems of Electric Balanced Forklifts

Xu,

Sui,

et al. 2023

Applied Sciences

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Similar to many complex systems, the operation process of electric balanced forklifts has characteristics such as time-varying model parameters and nonlinearity. Establishing an accurate mathematical model becomes challenging, making it difficult to apply model-based control methods in engineering practice. Aiming at the longitudinal control system of electric forklifts containing external disturbances, this paper proposes an improved full-format dynamic linearization model-free adaptive PID control (iFFDL-MFA-PID) method. Firstly, the full-format dynamic linearization (FFDL) method is employed to transform the operating system of the electric balanced forklift into a virtual equivalent linear data model. Secondly, the nonlinear residual term and pseudo-gradient (PG) of the data model are estimated using the difference estimation algorithm and the optimal criterion function, respectively. Furthermore, in order to enhance the robustness of the system, the idea of intelligent PID (iPID) is introduced and the principle of equivalent feedback is utilized to derive the iFFDL-MFA-PID control scheme. The design process of this scheme only requires the use of the input and output data of the system, without relying on the mathematical model of the system. Finally, the iFFDL-MFA-PID method proposed in this paper is simulated and tested with the EFG-BC/320 counterbalanced forklift equipped in the Special Equipment Testing Center and compared with the model-free adaptive control method (FFDL-MFAC) and the PID control method. Simulation results show that the speed-tracking error of the electric forklift truck under the action of the iFFDL-MFA-PID algorithm is maintained within ±0.132 m/s throughout the process, achieving higher tracking accuracy and better robustness compared to the MFAC and PID methods.

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Unstable Systems as a Challenging Benchmark for Control Engineering Students

Gazdoŝ

Charous

2022

Innovations in Mechatronics Engineering II

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Fuzzy fractional-order PID control for two-wheeled self-balancing robots on inclined road surface

Cited by 9 publications

References 22 publications

Speed regulation of electric vehicle motor based on PID control

Speed regulation of electric vehicle motor based on PID control

A Novel Model-Free Adaptive Proportional–Integral–Derivative Control Method for Speed-Tracking Systems of Electric Balanced Forklifts

Unstable Systems as a Challenging Benchmark for Control Engineering Students

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