An adaptive backstepping sliding mode control is proposed for a class of uncertain nonlinear systems with input saturation.A command filtered approach is used to prevent input saturation from destroying the adaptive c...An adaptive backstepping sliding mode control is proposed for a class of uncertain nonlinear systems with input saturation.A command filtered approach is used to prevent input saturation from destroying the adaptive capabilities of neural networks (NNs).The control law and adaptive updating laws of NNs are derived in the sense of Lyapunov function,so the stability can be guaranteed even under the input saturation.The proposed control law is robust against the disturbance,and it can also eliminate the impact of input saturation.Simulation results indicate that the proposed controller has a good performance.展开更多
In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear un...In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.展开更多
针对一类具有未知函数控制增益的多输入多输出(M IM O)非线性系统,基于后推设计方法和动态面控制技术,提出一种间接自适应神经网络控制方案.该方案通过引入1阶滤波器,消除了后推设计中由于反复对虚拟控制的求导而导致的复杂性问题,并避...针对一类具有未知函数控制增益的多输入多输出(M IM O)非线性系统,基于后推设计方法和动态面控制技术,提出一种间接自适应神经网络控制方案.该方案通过引入1阶滤波器,消除了后推设计中由于反复对虚拟控制的求导而导致的复杂性问题,并避免了反馈线性化方法可能出现的控制器奇异性问题,参数估计无需使用投影算法.利用李亚普诺夫方法,证明了闭环系统半全局一致终结有界,通过适当选取设计常数,跟踪误差可收敛到原点的一个小邻域内.仿真结果表明了该方法的有效性.展开更多
在多输入多输出(Multiple-input multiple-output,MIMO)非线性系统的执行器故障容错控制问题中,控制器能够处理的执行器故障集合的大小与执行器分组方法有很大关系.为扩大系统可处理的执行器故障集合,本文针对一类具有执行器故障的MIMO...在多输入多输出(Multiple-input multiple-output,MIMO)非线性系统的执行器故障容错控制问题中,控制器能够处理的执行器故障集合的大小与执行器分组方法有很大关系.为扩大系统可处理的执行器故障集合,本文针对一类具有执行器故障的MIMO非线性最小相位系统,提出基于多模型切换(Multiple model switching and tuning,MMST)执行器分组的自适应补偿控制方法.考虑系统的执行器卡死、部分失效和完全失效故障,在微分几何反馈线性化的基础上,研究基于多模型切换的执行器分组切换指标和切换策略,设计了基于反演控制的自适应补偿跟踪控制律,所设计的控制律能保证系统在执行器故障时闭环稳定,渐近跟踪给定的参考信号,且提出的分组方法扩大了可补偿的执行器故障集合.仿真结果表明了本文设计方法的有效性.展开更多
基金Supported by National Natural Science Foundation of China(No. 60674019,No. 61074088)
文摘An adaptive backstepping sliding mode control is proposed for a class of uncertain nonlinear systems with input saturation.A command filtered approach is used to prevent input saturation from destroying the adaptive capabilities of neural networks (NNs).The control law and adaptive updating laws of NNs are derived in the sense of Lyapunov function,so the stability can be guaranteed even under the input saturation.The proposed control law is robust against the disturbance,and it can also eliminate the impact of input saturation.Simulation results indicate that the proposed controller has a good performance.
文摘In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.
基金This research is supported by the National Nature Science Foundation of China under Grant No.60574007the Nature Science Foundation of Shandong Province under Grant No.Y2003G02.
基金Supported by National Outstanding Youth Science Foundation(61125306)National Natural Science Foundation(61473324)+2 种基金Beijing Higher Education Young Elite Teacher Project(YETP0378)Fundamental Research Funds for the Central Universities(FRF–TP–14–118A2)Beijing Natural Science Foundation(4154079)
文摘针对一类具有未知函数控制增益的多输入多输出(M IM O)非线性系统,基于后推设计方法和动态面控制技术,提出一种间接自适应神经网络控制方案.该方案通过引入1阶滤波器,消除了后推设计中由于反复对虚拟控制的求导而导致的复杂性问题,并避免了反馈线性化方法可能出现的控制器奇异性问题,参数估计无需使用投影算法.利用李亚普诺夫方法,证明了闭环系统半全局一致终结有界,通过适当选取设计常数,跟踪误差可收敛到原点的一个小邻域内.仿真结果表明了该方法的有效性.
文摘在多输入多输出(Multiple-input multiple-output,MIMO)非线性系统的执行器故障容错控制问题中,控制器能够处理的执行器故障集合的大小与执行器分组方法有很大关系.为扩大系统可处理的执行器故障集合,本文针对一类具有执行器故障的MIMO非线性最小相位系统,提出基于多模型切换(Multiple model switching and tuning,MMST)执行器分组的自适应补偿控制方法.考虑系统的执行器卡死、部分失效和完全失效故障,在微分几何反馈线性化的基础上,研究基于多模型切换的执行器分组切换指标和切换策略,设计了基于反演控制的自适应补偿跟踪控制律,所设计的控制律能保证系统在执行器故障时闭环稳定,渐近跟踪给定的参考信号,且提出的分组方法扩大了可补偿的执行器故障集合.仿真结果表明了本文设计方法的有效性.
