This paper proposes a decoupling control scheme with two-degrees-of-freedom (2DOF) control structure. In the proposed scheme, two multivariable controllers are designed based on Internal Model Control (IMC) theory for setpoint tracking and disturbance rejection independently. An analytical approximation method is utilized to reduce the order of the controllers. By adjusting the corresponding controller parameter, the setpoint tracking and disturbance rejection of each control loop can be tuned independently. In the presence of multiplicative input uncertainty, a calculation method is also proposed to derive the low bounds of the control parameters in order to guarantee the robust stability of the system. Simulations are illustrated to demonstrate the validity of the proposed control scheme.
This paper is concerned with the problem of robust H∞ control for structured uncertain stochastic neural networks with both discrete and distributed time varying delays. A sufficient condition is presented for the existence of H∞ control based on the Lyapunov stability theory. The stability criterion is described in terms of linear matrix inequalities （LMIs）, which can be easily checked in practice. An example is provided to demonstrate the effectiveness of the proposed result.
针对在高速网络中,传播时延对二进制ABR(Available Bit Rate)业务网络流量控制的不利影响,提出了一个新颖的2自由度控制结构作为拥塞的判定机制.这种控制机制不仅能克服原标准明晰前向拥塞指示(EFCI)算法中因存在带磁滞环的非线性环节引起的大幅振荡,而且在较大时延情况下仍能保持很好的给定值响应和抗干扰性能,同时可简单直接地对流控系统进行设计和调节.仿真结果验证了该控制方案的优越性.
