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Based on variable structure system theory and sliding mode, we develop an identification scheme suitable for time-varying parameters. The new identification scheme, working in closed-loop, addresses several key issues in system identification simultaneously: unstable process, highly nonlinear and uncertain dynamics, fast time varying parameters and rational nonlinear in the parametric space. Other important issues associated with identification, such as the persistent excitation property and insensitivity to measurement noise, are also discussed. A robotic manipulator is used as the illustrative example and the basis for comparison. [Copyright &y& Elsevier]

This paper proposes a novel adaptive output observer method for the distributed output tracking control of heterogeneous systems. Unlike the existing adaptive distributed state observer, an output-based adaptive distributed output observer (OADOO) that only relies on the leader's output is proposed to estimate the leader's information. Meanwhile, an input-based triggering mechanism is exploited to avoid continuous interactions between agents, and between the leader and its neighboring agents, respectively. Then, a local controller is developed to achieve the output tracking control. In comparison with the existing results for the similar research problem, our results not only handle the tracking control subject to only relative output measurement, but also considerably lower the data exchange traffic and dimension among agents of the developed OADOO. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the robust filtering problem is investigated for networked stochastic systems with norm bounded uncertainties and imperfect multiple transmitted measurements. The considered imperfect measurements contain randomly occurring sensor nonlinearities and packet dropouts, which are represented by multiple independent Markov chains with partially unknown transition probabilities. A one to one mapping is constructed to map the multiple independent Markov chains to an augmented one for facilitating the resultant system analysis. A sufficient condition is established to guarantee the exponential mean-square stability with fast decay rate and a certain performance level of the filtering error systems. Then, the parameters of the full-order filter are expressed in terms of linear matrix inequalities (LMIs). Finally, a numerical example is shown to demonstrate the effectiveness of the proposed method. [Copyright &y& Elsevier]

In this paper, via describing function techniques, sliding mode control of DC servo mechanisms is analyzed in the presence of unmodeled dynamics. We first show that, a conventional sliding mode controller with signum function will inevitably generate a limit cycle where a second or higher order unmodeled dynamics exists. A fractional interpolation based smoothing scheme is then proposed to eliminate the limit cycle, and maintain a reasonable tracking precision bound. In particular, a DC servo motor with unmodeled stator and sensor dynamics is taken into consideration. Both theoretical analysis and simulation results verify the effectiveness of the proposed new fractional interpolation control scheme. [Copyright &y& Elsevier]