Riccardo Marino

Brief Robust adaptive compensation of biased sinusoidal disturbances with unknown frequency

Asymptotically stable, observable linear systems of order n which are not required to be minimum phase and are affected by an additive noisy biased sinusoidal disturbance with unknown bias, magnitude, phase and frequency are considered. The problem of designing an output feedback compensator which regulates the output to zero for any initial condition and for any biased sinusoidal disturbance with no noise is addressed, under the assumption that the system parameters are known. This problem is solved by a (2n+6)-order compensator which generates asymptotically convergent estimates of the biased sinusoidal disturbance and of its parameters, including frequency. The robustness of the closed loop system with respect to sufficiently small additive unmodelled noise is characterized in terms of input-to-state stability.

On the largest feedback linearizable subsystem

Abstract A feedback invariant set of integers is associated with any nonlinear multivariable system which is linear with respect to the inputs: it is shown to be the set of controllability indices of the largest feedback linearizable subsystem, i.e. the largest subsystem which can be made locally linear and controllable by means of nonsingular feedback transformations.

A global tracking control for speed-sensorless induction motors

The problem of controlling an induction motor without rotor speed measurements is addressed. Arbitrary smooth reference signals for rotor speed and rotor flux modulus are required to be tracked globally (i.e. from any initial condition). A global second-order tracking control is obtained, which is based on a novel rotor speed observer. Simulation results are provided which illustrate the controller performance.

Brief paper: An adaptive tracking control from current measurements for induction motors with uncertain load torque and rotor resistance

The problem of controlling sensorless induction motors with uncertain constant load torque and rotor resistance on the basis of stator current measurements only is addressed. A new eighth-order dynamic nonlinear adaptive control algorithm is designed, which relies on a closed loop adaptive observer for the unmeasured state variables (rotor speed and fluxes) and for the uncertain parameters and is not based on non-robust open loop integration of flux dynamics. Local exponential stability of the closed loop tracking and estimation error dynamics is achieved under persistency of excitation conditions which restrict the reference signals and may be interpreted in terms of motor observability and rotor resistance identifiability.

A nonlinear tracking control for sensorless induction motors

We consider the tracking control problem for induction motors in which only stator currents and voltages are available for feedback. Local exponential rotor speed and rotor flux tracking is achieved for any initial condition belonging to an explicitly computable domain of attraction. Simulation results are reported.

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters. The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced. For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.

Learning control for nonlinear systems in output feedback form

Abstract The class of single-input, single-output, minimum phase, nonlinear, time-invariant systems with unknown output-dependent nonlinearities, unknown parameters and known relative degree ρ is considered. The output regulation problem is addressed and solved in the presence of unknown periodic reference and/or disturbance signals of known common period. A simple learning control algorithm is designed which guarantees asymptotic output tracking for any initial condition belonging to any given connected compact set. It can be interpreted as a generalization of the classical PID ρ − 1 control which solves the regulator problem when reference and disturbance signals are constant. As far as linear systems are concerned, global results are achieved.

Adaptive Field-oriented Control of Synchronous Motors with Damping Windings

Two different nonlinear dynamic control algorithms are presented for synchronous motors with damping windings: (i) an adaptive speed-sensorless controller for rotor position tracking in the presence of unknown constant load torque, on the basis of rotor angle, stator and field windings currents measurements; (ii) an adaptive control law for rotor speed tracking in the presence of uncertain constant load torque and motor inertia, which is based on measurements of mechanical variables (rotor angle and speed) and stator windings currents but does not require field current. As in classical field oriented control, the three voltage inputs are designed so that the direct axis component of the stator current vector is driven to zero; the controllers generate, as an intermediate step, the reference signals for the field current and for the quadrature axis component of the stator current vector, which respectively determine the direct axis component of the damping winding flux vector and the electromagnetic torque. Simulation results are provided for a 20-KW synchronous machine, which show the effectiveness of the two proposed control algorithms.

A NEW GLOBAL CONTROL SCHEME FOR SENSORLESS CURRENT-FED INDUCTION MOTORS

Abstract The problem of controlling a sensorless induction motor (i.e. without rotor speed measurements) is addressed. Smooth reference signals for rotor speed and rotor flux modulus are required to be tracked exponentially and globally. Only semiglobal solutions have been recently obtained in the literature. A global solution is presented for current-fed induction motors which makes use of a novel rotor speed observer and can be naturally extended to the full-order model.

Nonlinear tracking control for sensorless induction motors

We consider the tracking control problem for induction motors in which only stator currents and voltages are available for feedback. Local exponential rotor speed and rotor flux tracking is achieved for any initial condition belonging to an explicitly computable domain of attraction. Simulation results are reported.