This work has two primary objectives. First, it presents a state prediction strategy for a class of nonlinear Lipschitz systems subject to constant time delay in the input signal. As a result of a suitable change of variable, the state predictor asymptotically provides the value of the state units of time ahead. Second, it proposes a solution to the stabilization and trajectory tracking problems for the considered class of systems using predicted states. The predictor-controller convergence is proved by considering a complete Lyapunov functional. The proposed predictor-based controller strategy is evaluated using numerical simulations.

In this paper, the trajectory-tracking control problem of an omnidirectional mobile robot (also known as a type (3,0)) is addressed and solved. The proposed controller takes into account the mobile robot dynamic model and it is based on a particular passivity-based control formulation, widely applied in power electronics, resulting in linear time-varying controllers. It is formally proved that the proposed control strategy allows the exponentially asymptotic convergence of the tracking errors to zero and assures closed loop stability. The proposed tracking strategy is evaluated by numerical simulations and compared with the well known Computed-Torque control strategy, exhibiting an improved performance.

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In this paper we address the attitude estimation problem, with respect to the gravity vector, for mobile robots moving on a rough terrain. The proposed algorithm is based on the immersion and invariance technique. The performance of the proposed estimation algorithm is evaluated experimentally on a low cost mobile robot equipped with an inertial measurement unit.