基于自适应非奇异智能终端滑模观测器的风力机载荷增广预测控制

为有效降低风力机在高风速运行时的不平衡载荷,提出一种基于自适应非奇异智能终端滑模观测器的载荷增广预测控制策略。首先,针对模型不匹配导致的模型预测控制性能下降的问题,将指令跟踪误差与系统状态的变化量增广为状态向量,设计增广预测模型以消除稳态跟踪误差;其次,设计自适应非奇异终端滑模观测器对系统状态进行估计,以提高控制系统的可靠性;然后,设计多目标变速灰狼优化算法同时对控制器和观测器参数寻优;最后,基于Simulink仿真平台验证了所提控制策略的有效性。结果表明,所提控制策略可有效消除稳态误差,缩短调节时间并提高控制性能。

AUGMENTED PREDICTIVE INTELLIGENT CONTROL OF WIND TURBINE LOAD BASED ON ADAPTIVE NONSINGULAR TERMINAL SLIDING MODE OBSERVER

An augmented predictive intelligent control strategy of wind turbine load based on adaptive nonsingular terminal sliding mode observer（ANTSMO） is proposed to effectively reduce the unbalanced load. Firstly, aiming at the performance degradation of model predictive control（MPC） caused by model mismatch, the command tracking error and the change of state are augmented to state vector, and the augmented MPC is designed to eliminate the steady-state tracking error. Secondly, an ANTSMO is designed to estimate the state parameters, which can improve the reliability of the control system. Then, the multi-objective variable speed grey wolf optimization（MOVGWO） algorithm is designed to optimize the controller parameters. Finally, the effectiveness of the proposed control strategy is verified based on Simulink platform. The results show that the proposed control strategy can effectively eliminate the steady-state error, shorten the regulation time and improve the control performance.