Parameter identification of fractional order linear system based on Haar wavelet operational matrix.

Fractional order systems can be more adequate for the description of dynamical systems than integer order models, however, how to obtain fractional order models are still actively exploring. In this paper, an identification method for fractional order linear system was proposed. This is a method based on input-output data in time domain. The input and output signals are represented by Haar wavelet, and then fractional order systems described by fractional order differential equations are transformed into fractional order integral equations. Taking use of the Haar wavelet operational matrix of the fractional order integration, the fractional order linear system can easily be converted into a system of algebraic equation. Finally, the parameters of the fractional order system are determined by minimizing the errors between the output of the real system and that of the identified system. Numerical simulations, involving integral and fractional order systems, confirm the efficiency of the above methodology.

H2 control of linear uncertain systems considering input quantization with encoder/decoder mismatch.

In this paper, an H2 control design for linear uncertain systems with input quantization in the presence of more general encoder/decoder mismatch is investigated. The construction of the control law includes two parts: linear part and nonlinear part. The gain of the linear part is derived from linear matrix inequalities (LMIs), and the linear part of the control law is designed for achieving the H2 performance against system characteristic matrix uncertainty and encoder/decoder mismatch. The nonlinear part is designed to eliminate the influence of external disturbance and quantization error. Finally, examples are provided to illustrate the effectiveness of the proposed method.