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This paper proposes a novel unknown input observer (UIO) design approach to detect and isolate the actuator faults in finite frequency domain. Instead of completely rejecting the disturbance or noise of traditional UIOs, we exclude certain controlled inputs from the residuals. Meanwhile, knowledge on the disturbance/noise, such as frequency and statistical characteristics, is embedded into the design...
This paper is devoted to study the absolute exponential stability of recurrent neural network with novel generalized activation function, which is recently proposed in my previous paper. By integrating Lyapunov stability theory and LMI approach, the stability criterion is derived, which is in form of LMI with slack variables. It may enlarge the range in selecting neural networks?? parameters. Moreover,...
This paper mainly discusses the residual generation problem for discrete-time polynomial nonlinear systems with unknown inputs. By employing state-dependent polynomial Lyapunov functions, sufficient conditions for fault detection using lscr2-gain performance indices are presented in terms of nonlinear matrix inequalities (NMIs). We show that those NMIs can be solved by the recently developed technique...
In this paper, we discuss the fault detection with unknown inputs for a class of discrete-time piecewise linear systems. Piecewise linear systems are mostly partitioned based on their state variables. Due to the system noise and estimation errors, the transitions of actual state and its estimate may not be synchronized, as well as the system modes. Motivated by the recent works [31], [29], [32], [30],...
In this paper, we discuss the fault detection with unknown inputs for a class of continuous-time piecewise linear systems. Piecewise linear systems are mostly partitioned based on their state variables. Due to the system noise and estimation errors, the transitions of actual state and its estimate may not be synchronized, as well as the system modes. Hence, we consider the fault detection problem...
In this paper, we discuss the simultaneous stabilization and robust control for a class of polynomial systems. By employing state-dependent polynomial Lyapunov functions, sufficient conditions for stabilization with and without Hinfin performance are presented. These conditions can be verified by the recently developed technique named as sum of squares (SOS), which essentially is an LMI feasibility...
In this paper, we propose a scaling linear matrix inequality (LMI) approach to static output feedback control of discrete-time linear time invariant (LTI) plants. Based on whether the system matrix B or C is full-rank, we provide several different methods with respect to the system state dimension, output dimension and input dimension. These methods require a preprocessing to transfer B or C to a...
This paper is devoted to stability analysis of a novel delayed neural network, whose neurons are connected with each other through both neurons' feedback connection strength matrix and direct connection strength matrix. Both delay-independent and delay-dependent stability criteria are obtained with Lyapunov-Krasovskii functional method. The criteria are in form of LMI with more slack variables, which...
This work is motivated by some recent works on dilated LMI characterization (M.C. de Oliveira et al., 1999), (M.C. de Oliveira and R.E. Skelton, 2001), (D. Peaucelle et al., 2000) and sums-of-squares Lyapunov functions (J. Xu and L. Xie, 2005), (G. Chesi et al., 2003), as well as duality theory (R. Goebel et al., 2004), (A. Rantzer, 2001), (R. Goebel et al., 2005). The paper is divided into two parts...
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