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This paper investigates the minimum data rate over a lossy channel for the mean square stabilization of single input discrete linear time-invariant (LTI) systems. The channel is subject to a packet dropout process, which is modeled as an independent and identically distributed (i.i.d.) process. The minimum data rate, which is explicitly given by unstable eigenvalues of the open loop matrix and the...
The concept of canalizing Boolean function is generalized to multi-input multi-output canalizing Boolean mapping. Using the semi-tensor product of matrices and the matrix expression of logical functions, an easily verifiable condition is provided for testing whether a Boolean mapping is a canalizing Boolean mapping. Using it, the disturbance decoupling problem (DDP) of Boolean control networks is...
The latest developments in complex network theory have provided a new direction for power system research. Based on this theory a power system can be modeled as a graph with nodes and vertices and further analysis can help in addressing typical problems such as identifying the vulnerable lines and pole fires, and locating faults. This paper reports some of our recent research in this area and discusses...
Control design for variable speed wind turbine system is one of most challenge to engineer today. Wind energy conversion system that includes complex combination of aero dynamics and electrical phenomena together with anonymous action of wind speed making control system sophisticated. Beside the nonlinearity model of wind turbine, the basic control strategy for wind turbine is maximizing the power...
The AFM system have been widely used in probing and imaging the surface property at atomic-resolution as well as measuring friction at the nanoscale. We present an analytic model of the AFM system that imitates the AFM tip as a 1D array of particles moving on a rigid substrate, and study its stability under a constant driving velocity. We reveal that both the center of the mass of the particle array...
This paper studies the stabilization problem for a class of stochastic nonlinear interconnected systems with unknown parameters involved. By employing filtered transformation, the stochastic Lyapunov-like theorem and the back-stepping design technique, a decentralized output-feedback controller and parameter adaptive law are proposed. It is proved that the closed-loop, large-scale, interconnected...
In this paper, we investigate identification of a class of distributed parameter systems (DPS) with both spatially invariant and spatially varying parameters via deterministic learning. The plant is a parabolic type partial differential equation (PDE) describing the propagation of heat conduction in a one-dimensional circle. We firstly employ the discrete Fourier transform (DFT) and the Inverse discrete...
In this paper we study the practical asymptotic stability for a class of discrete-time time-delay systems via Razumikhin-type Theorems. Further estimations of the solution boundary and arrival time of the solution are also investigated based on practical stability. In addition, the proposed theorems are used to analyze the practical controllability of a general class of nonlinear discrete systems...
In this paper, we aim to develop controllers for uncertain systems in the presence of possible actuator failures. A new scheme is proposed to design output feedback controllers for a class of uncertain systems having redundant actuators, with which the relative degrees of transfer functions are different. To deal with these actuators using backstepping technique, we introduce a pre-filter before each...
In this paper, we study the asymptotic tracking and disturbance rejection problem for a class of uncertain nonlinear lower triangular systems subject to an uncertain exosystem. The same problem was studied before for the same class of systems with the objective of asymptotic tracking only. By utilizing a newly developed robust adaptive controller design approach, we are able to simultaneously handle...
One of the fundamental problems in control systems is the estimation of the state variables of a dynamic system using available noisy measurements. State estimation methods in the minimum variance sense and in the min-max sense, i.e. H-infinity filtering, have been developed over the past decades, including the so-called robust filtering, namely state estimation methods which are based on an approximate...
Stabilization of uncertain dynamic systems is investigated focusing on plant models that involve both multiplicative and relative uncertainties that are bounded by H??-norm. A new notion of stability margin is proposed to study the robustness of the feedback stability. It is shown that the largest possible stability margin is a two-disk problem. An upper and lower bounds are derived which differ by...
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