• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.26-29
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• 2001

In a target tracking problem the radar glint noise has non-Gaussian heavy-tailed distribution and will seriously affect the target tracking performance. In most nonlinear situations an Extended Robust Kalman Filter(ERKF) can yield acceptable performance as long as the noises are white Gaussian. However, an Extended Robust $H_{\infty}$ Filter (ERHF) can yield acceptable performance when the noises are Laplacian. In this paper, we use the Interacting Multiple Model(IMM) estimator for the problem of target tracking with glint noise. In the IMM method, two filters(ERKF and ERHF) are used in parallel to estimate the state. Computer simulations of a real target tracking shows that hybrid filter used the IMM algorithm has superior performance than a single type filter.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2152-2154
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• 2004

A robust bending frequency tracker is proposed to design the adaptive notch filter which removes the time-varying missile structural mode from the sensor measurements. To design the bending frequency tracker, firstly, the signal model is derived from the input-output relationship of Nehorai notch filter structure. Also, the time-varying nature of the bending frequency is modelled as the norm-bounded uncertainty. Based on the uncertain signal model, it is shown that the design problem of robust bending frequency tracker can be casted into that of adaptive robust $H_{\infty}$ filter or equivalently robust LMS filter.

• Smart Structures and Systems
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• v.16 no.2
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• pp.329-345
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• 2015

As commonly known, sensor errors and faulty signals may potentially lead structures in vibration to catastrophic failures. This paper presents a new approach to deal with sensor errors/faults in vibration control of structures by using the Fault detection and isolation (FDI) technique. To demonstrate the effectiveness of the approach, a space truss structure with semi-active devices such as Magneto-Rheological (MR) damper is used as an example. To address the problem, a Linear Matrix Inequality (LMI) based fixed-order $H_{\infty}$ FDI filter is introduced and designed. Modeling errors are treated as uncertainties in the FDI filter design to verify the robustness of the proposed FDI filter. Furthermore, an innovative Fuzzy Fault Tolerant Controller (FFTC) has been developed for this space truss structure model to preserve the pre-specified performance in the presence of sensor errors or faults. Simulation results have demonstrated that the proposed FDI filter is capable of detecting and isolating sensor errors/faults and actuator faults e.g., accelerometers and MR dampers, and the proposed FFTC can maintain the structural vibration suppression in faulty conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.255-257
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• 2009

The robust stabilization problem of a multivariable uncertain system with a polytopic model is considered. A PI-type $H_{\infty}$ controller with a low pass filter is used for robust stabilization and noise rejection. The problem is reduced to an LMI optimization problem. A sufficient condition for the existence of the PI controller is derived in terms of LMIs. The PI gain matrices are parameterized by using the solution matrices to the existence conditions. Finally, a numerical design example is given.