4 research outputs found

    Variance-constrained state estimation for networked multi-rate systems with measurement quantization and probabilistic sensor failures

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    This paper is concerned with the variance-constrained state estimation problem for a class of networked multi-rate systems (NMSs) with network-induced probabilistic sensor failures and measurement quantization. The stochastic characteristics of the sensor failures are governed by mutually independent random variables over the interval [0,1]. By applying the lifting technique, an augmented system model is established to facilitate the state estimation of the underlying NMSs. With the aid of the stochastic analysis approach, sufficient conditions are derived under which the exponential mean-square stability of the augmented system is guaranteed, the prescribed H∞ performance constraint is achieved, and the individual variance constraint on the steady-state estimation error is satisfied. Based on the derived conditions, the addressed variance-constrained state estimation problem of NMSs is recast as a convex optimization one that can be solved via the semi-definite program method. Furthermore, the explicit expression of the desired estimator gains is obtained by means of the feasibility of certain matrix inequalities. Two additional optimization problems are considered with respect to the H∞ performance index and the weighted error variances. Finally, a simulation example is utilized to illustrate the effectiveness of the proposed state estimation method

    An adaptive type-2 fuzzy sliding mode tracking controller for a robotic manipulator

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    With the wide application of intelligent manufacturing and the development of diversified functions of industrial manipulator, the requirements for the control accuracy and stability of the manipulator servo system are also increasing. The control of industrial manipulator is a time-varying system with nonlinear and strong coupling, which is often affected by uncertain factors, including parameter changing, environmental interference, joint friction and so on. Aiming at the problem of the poor control accuracy of the manipulator. Under the complex disturbance environment, control accuracy of the manipulator will be greatly affected, so this paper proposes an adaptive type-2 fuzzy sliding mode control (AT2FSMC) method applied to the servo control of the industrial manipulator, which realizes the adaptive adjustment of the boundary layer thickness to suppress the trajectory error caused by the external disturbance and weakens the chattering problem of the sliding mode control. The simulation results on a two-axis manipulator indicate that, with the presence of external disturbances, the proposed control method can help the manipulator maintain control signal stability and improve tracking accuracy. It also suppressed chattering produced by sliding mode control (SMC) and strengthening the robustness of the system. Compared with other conventional trajectory tracking control methods, the effectiveness of the proposed method can be reflected. Finally, the proposed method is tested in an actual manipulator to complete a practical trajectory to prove its feasibility

    Fault-tolerant sliding-mode-observer synthesis of Markovian jump systems using quantized measurements

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    This paper investigates the design problem of sliding mode observer (SMO) using quantized measurements for a class of Markovian jump systems against actuator faults. Such a problem arises in modern networked-based digital systems, where data have to be transmitted and exchanged over a digital communication channel. In this paper, a new descriptor SMO approach using quantized signals is presented, in which a discontinuous input is synthesized to reject actuator faults by an offline static compensation of quantization effects. It is revealed that the lower bound on the density of a logarithmic quantizer is 1/3, under which the quantization effects could be compensated completely by using the SMO approach. Based on the proposed observer method, the asymptotical estimations of state vector and quantization errors can be obtained simultaneously. Finally, an example of a linearized model of an F-404 aircraft engine system is included to show the effectiveness of the presented observer design method.Peng Shi, Ming Liu, and Lixian Zhan
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