Author
Patrizio Tomei
Other affiliations: Instituto Politécnico Nacional, Sapienza University of Rome
Bio: Patrizio Tomei is an academic researcher from University of Rome Tor Vergata. The author has contributed to research in topics: Adaptive control & Nonlinear system. The author has an hindex of 42, co-authored 197 publications receiving 7779 citations. Previous affiliations of Patrizio Tomei include Instituto Politécnico Nacional & Sapienza University of Rome.
Papers published on a yearly basis
Papers
More filters
Book•
01 Jan 1996TL;DR: In this paper, the authors propose robust regulation and adaptive tracking for output feedback and output output tracking with adaptive observer and adaptive feedback linearization, and robust regulation for robust output feedback with adaptive tracking.
Abstract: STATE FEEDBACK. Feedback Linearization. Adaptive Feedback Linearization. Output Tracking. OUTPUT FEEDBACK. Adaptive Observers. Stabilization and Exponential Tracking. Robust Regulation and Adaptive Tracking.
925 citations
TL;DR: In this paper, the point-to-point control of a manipulator with three revolute elastic joints is considered and it is shown that a simple PD controller, similar to that used for rigid robots, suffices to globally stabilize the elastic joint robots about a reference position.
Abstract: The point-to-point control of manipulators having elastic joints is considered. It is shown that a simple PD (proportional plus derivative) controller, similar to that used for rigid robots, suffices to globally stabilize the elastic joint robots about a reference position. A robustness analysis is also given with respect to uncertainties on the robot parameters. The results of numerical simulation tests of a manipulator with three revolute elastic joints are presented. >
539 citations
TL;DR: In this paper, an observer for reconstructing the joint velocities of rigid-joint robots is proposed, which consists of exploiting the structural properties of the robot dynamics and is shown to be asymptotically stable.
Abstract: An observer for reconstructing the joint velocities of rigid-joint robots is proposed. The approach consists of exploiting the structural properties of the robot dynamics. The associated error dynamics are shown to be asymptotically stable. The observer furnishes the state estimate directly in the physical coordinates, so that no transformation is needed. The stability of some state feedback controllers having the proposed observer inserted in the feedback loop is proved. The structure of the observer and its convergence are shown. The stability of the whole system is analyzed when the observer is used in connection with a point-to-point controller and a trajectory controller. >
424 citations
Book•
01 Jan 1995TL;DR: Stabilization and Exponential Tracking.
Abstract: STATE FEEDBACK. Feedback Linearization. Adaptive Feedback Linearization. Output Tracking. OUTPUT FEEDBACK. Adaptive Observers. Stabilization and Exponential Tracking. Robust Regulation and Adaptive Tracking.
318 citations
TL;DR: The adaptive observers presented in this note guarantee arbitrarily fast exponential convergence both of parameter and state estimates to actual parameters and states, while previous adaptive observers guarantee only exponential (not arbitrarily fast) convergence.
Abstract: Concerns the same class of linearly parameterized single-output nonlinear systems that the authors previously identified in (1992) in terms of differential geometric conditions. When persistency of excitation conditions are satisfied, the adaptive observers presented in this note guarantee arbitrarily fast exponential convergence both of parameter and state estimates to actual parameters and states, while previous adaptive observers guarantee only exponential (not arbitrarily fast) convergence. This extends earlier results for linear systems. >
284 citations
Cited by
More filters
TL;DR: This paper presents control designs for single-input single-output (SISO) nonlinear systems in strict feedback form with an output constraint, and explores the use of an Asymmetric Barrier Lyapunov Function as a generalized approach that relaxes the requirements on the initial conditions.
1,999 citations
TL;DR: This work addresses the problem of global asymptotic stabilization via partial-state feedback for linear systems with nonlinear, stable dynamic perturbations and for systems which have a particular disturbed recurrent structure.
Abstract: We introduce a concept of input-to-output practical stability (IOpS) which is a natural generalization of input-to-state stability proposed by Sontag. It allows us to establish two important results. The first one states that the general interconnection of two IOpS systems is again an IOpS system if an appropriate composition of the gain functions is smaller than the identity function. The second one shows an example of gain function assignment by feedback. As an illustration of the interest of these results, we address the problem of global asymptotic stabilization via partial-state feedback for linear systems with nonlinear, stable dynamic perturbations and for systems which have a particular disturbed recurrent structure.
1,349 citations
TL;DR: A review of recently used direct torque and flux control techniques for voltage inverter-fed induction and permanent-magnet synchronous motors and trends in the DTC-SVM techniques based on neuro-fuzzy logic controllers are presented.
Abstract: This paper presents a review of recently used direct torque and flux control (DTC) techniques for voltage inverter-fed induction and permanent-magnet synchronous motors. A variety of techniques, different in concept, are described as follows: switching-table-based hysteresis DTC, direct self control, constant-switching-frequency DTC with space-vector modulation (DTC-SVM). Also, trends in the DTC-SVM techniques based on neuro-fuzzy logic controllers are presented. Some oscillograms that illustrate properties of the presented techniques are shown.
1,200 citations
TL;DR: In this paper, the adaptive control of minimum-phase nonlinear systems which are exactly input-output linearizable by state feedback is discussed. But the application of the adaptive technique to control of robot manipulators is discussed only in the continuous-time case.
Abstract: The authors give some initial results on the adaptive control of minimum-phase nonlinear systems which are exactly input-output linearizable by state feedback. Parameter adaptation is used as a technique to make robust the exact cancellation of nonlinear terms, which is called for in the linearization technique. The application of the adaptive technique to control of robot manipulators is discussed. Only the continuous-time case is considered; extensions to the discrete-time and sampled-data cases are not obvious. >
1,182 citations
TL;DR: The input-to-state stability property and small-gain theorems are introduced as the cornerstone of new stability criteria for discrete-time nonlinear systems.
1,179 citations