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In this paper, a proportional observer design using quadratic boundedness is proposed in order to estimate the state of a system described by a Takagi-Sugeno model with a Lipschitz nonlinearity term, and affected by unknown disturbances. The conditions for ensuring that the error between the real and the estimated state converge within an ellipsoidal region about zero, are provided in the form of a linear matrix inequality (LMI) formulation. Then, the simulation results of this approach applied to a four-wheeled omni-directional mobile robot will be shown.

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In this paper, a model reference control strategy is proposed in order to perform trajectory tracking in Takagi–Sugeno–Lipschitz (TSL) systems. Since the state vector is assumed not to be completely available for measurement, a proportional observer is added to the control scheme in order to apply an estimate‐feedback control action instead of a state‐feedback one. The overall design of both the controller and the observer gains are performed using a Lyapunov‐based quadratic boundedness specification, in order to improve the robustness against unknown exogenous disturbances. It is shown that the conditions that ensure convergence within ellipsoidal regions of the tracking and estimation errors can be expressed in the form of a linear matrix inequality (LMI) formulation. The effectiveness of the developed control strategy is demonstrated by means of simulation results.