Properties of the nonlinear transfer function are studied in this paper and the n-th order stabili-ty, n-th order frequency response and n-th order sensitivity as well as a novel theory and implementationon the sensit...Properties of the nonlinear transfer function are studied in this paper and the n-th order stabili-ty, n-th order frequency response and n-th order sensitivity as well as a novel theory and implementationon the sensitivity of nonlinear transfer system are proposed.展开更多
This paper explores the adaptive iterative learning control method in the control of fractional order systems for the first time. An adaptive iterative learning control(AILC) scheme is presented for a class of commens...This paper explores the adaptive iterative learning control method in the control of fractional order systems for the first time. An adaptive iterative learning control(AILC) scheme is presented for a class of commensurate high-order uncertain nonlinear fractional order systems in the presence of disturbance.To facilitate the controller design, a sliding mode surface of tracking errors is designed by using sufficient conditions of linear fractional order systems. To relax the assumption of the identical initial condition in iterative learning control(ILC), a new boundary layer function is proposed by employing MittagLeffler function. The uncertainty in the system is compensated for by utilizing radial basis function neural network. Fractional order differential type updating laws and difference type learning law are designed to estimate unknown constant parameters and time-varying parameter, respectively. The hyperbolic tangent function and a convergent series sequence are used to design robust control term for neural network approximation error and bounded disturbance, simultaneously guaranteeing the learning convergence along iteration. The system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapnov-like composite energy function(CEF)containing new integral type Lyapunov function, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach.展开更多
文摘Properties of the nonlinear transfer function are studied in this paper and the n-th order stabili-ty, n-th order frequency response and n-th order sensitivity as well as a novel theory and implementationon the sensitivity of nonlinear transfer system are proposed.
基金supported by the National Natural Science Foundation of China(60674090)Shandong Natural Science Foundation(ZR2017QF016)
文摘This paper explores the adaptive iterative learning control method in the control of fractional order systems for the first time. An adaptive iterative learning control(AILC) scheme is presented for a class of commensurate high-order uncertain nonlinear fractional order systems in the presence of disturbance.To facilitate the controller design, a sliding mode surface of tracking errors is designed by using sufficient conditions of linear fractional order systems. To relax the assumption of the identical initial condition in iterative learning control(ILC), a new boundary layer function is proposed by employing MittagLeffler function. The uncertainty in the system is compensated for by utilizing radial basis function neural network. Fractional order differential type updating laws and difference type learning law are designed to estimate unknown constant parameters and time-varying parameter, respectively. The hyperbolic tangent function and a convergent series sequence are used to design robust control term for neural network approximation error and bounded disturbance, simultaneously guaranteeing the learning convergence along iteration. The system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapnov-like composite energy function(CEF)containing new integral type Lyapunov function, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach.
文摘不经意传输(OT,oblivious transfer)协议是密码学中的一个基本协议。基于物理不可克隆函数(PUF,physical unclonable function)给出物理不可克隆函数系统(PUFS,physical unclonable function system)的概念,并在此基础上提出一个新的不经意传输协议(POT,PUFS based OT),最后在通用可组合(UC,universal composition)框架内给出POT协议抵抗静态敌手的安全性证明。相比于传统基于公钥加密的OT方案,POT协议不使用任何可计算的假设,而是基于PUFS的安全属性实现,因此在很大程度上减小了计算和通信开销。
