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This paper addresses the design of robust multiple model adaptive controllers (RMMAC) for linear parameter varying (LPV) systems using bilinear matrix inequalities (BMI). We show a novel method that allows increasing the performance of the RMMAC when the uncertain parameters of the system dynamics are time-varying (TV). We assume that these TV parameters cannot be measured on-line and that the only...
This paper addresses the problem of attitude and rate gyro bias estimation using Set-Valued Observers (SVOs). We propose a singularity-free solution that exploits rate gyro measurements and vector observations corrupted by bounded noise providing bounds on the attitude of the rigid body and on the bias of the rate gyros. The sensor readings are fused directly by the SVO, without intermediate attitude...
An optimal Set-Valued Observer (SVO) for attitude estimation that merges rate gyro readings with body frame vectorial observations is proposed. The observer provides singularity-free estimates and considers sensor readings corrupted by bounded (but unknown) measurement noise. The suggested solution is an alternative method to the ones available in the literature, with the guarantee that the state...
This paper introduces the novel concept of using Set-Valued Observers (SVOs) in Fault Detection and Isolation (FDI), for discrete-time linear time-varying systems. The proposed method relies on SVO-based model invalidation to discard models that are not compatible with the input/output data. We argue that there are mainly three significant advantages of using SVOs for FDI, when compared to the most...
This paper addresses the problem of robust takeoff and landing control of a quadrotor UAV (Unmanned Aerial Vehicle). During the critical flight phases of takeoff and landing the vehicle dynamics change according to the possible existence of contact with the ground. To model the vehicle during the overall maneuver a hybrid automaton is used where each state corresponds to a different dynamic behavior...
The problem of model falsification or model invalidation appears in several areas where we are interested in distinguishing among an eligible set of dynamic systems. In the context of fMRI studies of brain activity, modeling the haemodynamic response function (HRF) is a critical step. The estimation of the dynamic system describing a biophysical model of the HRF may leave much uncertainty on the exact...
This paper proposes a multiple-model adaptive control methodology, using set-valued observers (MMAC-SVO) for the identification subsystem, that is able to provide robust stability and performance guarantees for the closed-loop, when the plant, which can be open-loop stable or unstable, has significant parametric uncertainty. We illustrate, with an example, how set-valued observers (SVOs) can be used...
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