Fuzzy PID Combined with Smith Predictor Control of GSHP Terminal Fan System

Chen, Shijun; Fei, Yue; Zheng, Songsong; Peng, Kang; Zhang, Tao; Yang, Qinmin

doi:10.1109/iccss52145.2020.9336829

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…The Adding controllers and filters to the feedback path is used to improve model parameter mismatch [5]. Fuzzy PID with Smith's Using fuzzy PID in combination with Smith predictors to increase the adaptivity and robustness of the control system [6] .The EHA is optimised according to a genetic algorithm to obtain the EHA. The optimal time lag feedback coefficients and time lags of the EHA suspension system are obtained by genetic algorithm optimisation, which is used as the optimal time lag feedback model to design the adaptive Smith feedback time lag control strategy [7].The adaptive Smith feedback time lag control strategy is designed using the optimal time lag feedback model.…”

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confidence: 99%

Research on Steering Balance Control of Two-wheeled Vehicles Under Large Time Delay

Wang,

Dan,

Peng

2023

AJST

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Time lag is very common in real control systems and is more important in driverless intelligent single rutted two-wheeled vehicles. Time lag can lead to slower response of the control system to external changes, which can reduce the stability or even imbalance of the vehicle. Traditional control methods may not be directly applicable to systems with time lag, so special control strategies are needed to deal with the effects of time lag. In this paper, we build a non-time-lagged steering balance controller by analysing the dynamics model of an unmanned intelligent single rutted two-wheeled vehicle, and then control the time lag by using the improved Smith predictor, and finally verify the steering balance of the method under large time lag by MATLAB simulation.

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confidence: 99%