A robust adaptive tracking control method is presented based on the fuzzy T-S model.
提出了一种基于T - S模糊模型和自适应神经网络的跟踪控制方法。
Robust adaptive tracking problems for a class of stochastic nonlinear systems were investigated.
研究了一类随机非线性系统的鲁棒自适应跟踪问题。
This paper proposed a new class of robust adaptive decentralized control strategies based on nonlinear sliding mode for trajectory tracking of robot manipulators with uncertainties.
提出了一类基于非线性滑动模的鲁棒自适应分散控制策略，用于不确定性机器人的轨迹跟踪。
An adaptive neural sliding mode control strategy with the self-tuning of robust item coefficients is proposed for the trajectory tracking of non-holonomic wheeled mobile robots.
针对非完整移动机器人的轨迹跟踪控制问题，提出了一种鲁棒项系数自调整的神经网络滑模自适应控制策略。
The experimental results show that the adaptive controller based on DRFNN can make electro-hydraulic position tracking system more robust and obtain satisfactory tracking performance.
实验结果表明：基于DRFNN的自适应控制器可使电液位置跟踪系统具有较强的鲁棒性和满意的跟踪性能。
The experimental results show that the adaptive controller based on DRFNN can make electro-hydraulic position tracking system more robust and obtain satisfactory tracking performance.
实验结果表明：基于DRFNN的自适应控制器可使电液位置跟踪系统具有较强的鲁棒性和满意的跟踪性能。
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