TY - GEN
T1 - Single neuron PID controller based on adaptive Smith predictor for networked control systems
AU - Zhang, Xian
AU - Yang, Liman
AU - Li, Yunhua
PY - 2012
Y1 - 2012
N2 - For networked control systems (NCS), the network-induced time delay with uncertain nature may degrade the control performance and even destabilize the system. Therefore, it is necessary to study the strategies to compensate time delay. In order to effectively restrain the impact of network time delay, a single neuron PID controller combined with adaptive Smith predictor is proposed to achieve better compensation effect in the paper. The traditional Smith predictor is sensitive to parameter uncertainties, leading to compensation failure when the time delay is stochastic. Single neuron PID controller is adopted to improve the adaptability and the robustness of system with the ability of self-learning and the simple structure. New adaptive Smith predictor can ensure the model error converge to zero. Besides, it does not include the delay model, thus the network time delay does not need to be measured or estimated. Simulation results are given to illustrate the effectiveness and the robustness of the proposed method.
AB - For networked control systems (NCS), the network-induced time delay with uncertain nature may degrade the control performance and even destabilize the system. Therefore, it is necessary to study the strategies to compensate time delay. In order to effectively restrain the impact of network time delay, a single neuron PID controller combined with adaptive Smith predictor is proposed to achieve better compensation effect in the paper. The traditional Smith predictor is sensitive to parameter uncertainties, leading to compensation failure when the time delay is stochastic. Single neuron PID controller is adopted to improve the adaptability and the robustness of system with the ability of self-learning and the simple structure. New adaptive Smith predictor can ensure the model error converge to zero. Besides, it does not include the delay model, thus the network time delay does not need to be measured or estimated. Simulation results are given to illustrate the effectiveness and the robustness of the proposed method.
KW - adaptive Smith predictor
KW - networked control systems
KW - single neuron PID controller
KW - time delay
UR - https://www.scopus.com/pages/publications/84868223892
U2 - 10.1109/INDIN.2012.6301217
DO - 10.1109/INDIN.2012.6301217
M3 - 会议稿件
AN - SCOPUS:84868223892
SN - 9781467303118
T3 - IEEE International Conference on Industrial Informatics (INDIN)
SP - 1136
EP - 1141
BT - INDIN 2012 - IEEE 10th International Conference on Industrial Informatics
T2 - IEEE 10th International Conference on Industrial Informatics, INDIN 2012
Y2 - 25 July 2012 through 27 July 2012
ER -