arXiv subjects

Shivaraj Mohite

Publications and source records attributed to Shivaraj Mohite.

3 recordsLinked to original sources

arXiv2026

Nonlinear parameter-varying embeddings for nonlinear state estimation with application to a two-link robot manipulator

Observer design for nonlinear systems is a relevant and challenging task in systems and control design. In this work, we follow the idea of embedding the system in the class of nonlinear parameter-varying systems to benefit from linear structures as in a standard LPV embedding while keeping some nonlinear structures and, thus, reducing the numbers of scheduling-parameters in the representation. We lay out the NLPV observer design procedure for general nonlinear systems, propose a number of improvements, and exemplify the application for a two-arm robot model. In a numerical study, we compare the performance of the NLPV design to established standard nonlinear approaches such as the \emph{extended Kalman filter} and the \emph{moving horizon estimation}.

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arXiv2024

Nonlinear Observer Design in Discrete-time Systems: Incorporating LMI Relaxation Strategies

This manuscript focuses on the $\mathcal{H}_\infty$ observer design for a class of nonlinear discrete systems under the presence of measurement noise or external disturbances. Two new Linear Matrix Inequality (LMI) conditions are developed in this method through the utilization of the reformulated Lipschitz property, a new variant of Young inequality and the well-known Linear Parameter Varying (LPV) approach. One of the key components of the proposed LMIs is the generalized matrix multipliers. The judicious use of these multipliers enables us to introduce more numbers of decision variables inside LMIs than the one illustrated in the literature. It aids in adding some extra degrees of freedom from a feasibility point of view, thus enhancing the LMI conditions. Thus, the established LMIs are less conservative than existing ones. Later on, the effectiveness of the developed LMIs and observer is highlighted through a numerical example and the application of state of charge (SoC) estimation in the Li-ion battery model.

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arXiv2023

Estimating the Faults/Attacks using a Fast Adaptive Unknown Input Observer: An Enhanced LMI Approach

This paper deals with the problem of robust fault estimation for the Lipschitz nonlinear systems under the influence of sensor faults and actuator faults. In the proposed methodology, a descriptor system is formulated by augmenting sensor fault vectors with the states of the system. A novel fast adaptive unknown input observer (FAUIO) structure is proposed for the simultaneous estimation of both faults and states of a class of nonlinear systems. A new LMI condition is established by utilizing the $\mathcal{H}_\infty$ criterion to ensure the asymptotic convergence of the estimation error of the developed observer. This derived LMI condition is deduced by incorporating the reformulated Lipschitz property, a new variant of Young inequality, and the well-known linear parameter varying (LPV) approach. It is less conservative than the existing ones in the literature, and its effectiveness is compared with the other proposed approaches. Further, the proposed observer methodology is extended for the disturbance-affected nonlinear system for the purpose of the reconstruction of states and faults with optimal noise attenuation. Later on, both designed approaches are validated through an application of a single-link robotic arm manipulator in MATLAB Simulink.

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