Sergei Peresada

Adaptive input-output linearizing control of induction motors

A nonlinear adaptive state feedback input-output linearizing control is designed for a fifth-order model of an induction motor which includes both electrical and mechanical dynamics under the assumptions of linear magnetic circuits. The control algorithm contains a nonlinear identification scheme which asymptotically tracks the true values of the load torque and rotor resistance which are assumed to be constant but unknown. Once those parameters are identified, the two control goals of regulating rotor speed and rotor flux amplitude are decoupled, so that power efficiency can be improved without affecting speed regulation. Full state measurements are required. >

On-line stator and rotor resistance estimation for induction motors

A ninth-order estimation algorithm is designed which provides online exponentially convergent estimates of both rotor and stator resistance for induction motors, when persistency of excitation conditions are satisfied and the stator current integrals are bounded, on the basis of rotor speed, stator voltages, and stator current measurements. Rotor flux is also asymptotically recovered. Experimental tests are reported which show that: persistency of excitation and boundedness of stator currents integrals hold in typical operating conditions; both resistance estimates converge exponentially to true values; the algorithm is implementable online by currently available digital signal processors; and the algorithm is robust with respect to modeling inaccuracies. The proposed estimation scheme is intended to improve performance and efficiency of currently available induction motor control algorithms.

Adaptive partial feedback linearization of induction motors

A nonlinear adaptive state feedback input-output linearizing control is designed for a fifth-order model of an induction motor which includes both electrical and mechanical dynamics under the assumptions of linear magnetic circuits. The control algorithm contains a nonlinear identification scheme which asymptotically tracks the true values of the load torque and rotor resistance, which are assumed to be constant but unknown. Once those parameters are identified, the two control goals of regulating rotor speed and rotor flux amplitude are decoupled. Full state measurements are required. Preliminary simulations show that a good performance is maintained when flux signals are provided to the adaptive control algorithm.<<ETX>>

Output feedback control of current-fed induction motors with unknown rotor resistance

On the basis of a third-order reduced model of an induction motor (current-fed) the authors design an output feedback control (from rotor speed measurements) which guarantees global exponential tracking of speed and rotor flux modulus reference signals. An adaptive version is designed when load torque is constant and unknown. The rotor resistance, which is a crucial parameter for the control, is updated by a seventh-order dynamic estimator designed on the basis of speed, current, and voltage signals. The estimator provides exponentially convergent estimates in physical operating conditions. A good performance of the adaptive control algorithm using a sampling time of 0.5 ms is documented by experimental tests. Experiments show that the main advantage of the proposed control with respect to the classical field oriented control algorithm is the decoupling of speed and flux tracking; in addition, efficiency is improved in presence of rotor resistance variations.

Nonlinear adaptive control of permanent magnet step motors

Abstract The problem of accurate positioning of permanent magnet step motors with sinusoidal flux distribution is considered. On the basis of a nonlinear model containing six unknown parameters, a nonlinear adaptive control is designed that guarantees asymptotic tracking of a desired angle reference signal, feeding back the whole state measurements (position, speed and currents). The algorithm may be used for preliminary on-line identification of those parameters that do not vary during operation: persistency of excitation conditions are given that guarantee identification with exponential convergence. When the only unknown parameters are load torque and stator resistance, which vary during operations, persistency of excitation conditions are satisfied when stator currents are not zero: in this case the adaptive control provides on-line exponential parameter estimation and exponential tracking of desired position signals. Simulations show the performance of the adaptive algorithm and a comparison with PID control.

Power control of a doubly fed induction machine via output feedback

Abstract A new output feedback control algorithm for a doubly fed induction machine (DFIM) is presented. The asymptotic regulation of active and reactive power is achieved by means of direct closed-loop control of active and reactive components of the stator current vector, presented in a line-voltage-oriented reference frame. To get the maximum generality of the solution, the usual assumption of negligible stator resistance is not made. A full-order DFIM model is used for the control algorithm development. The proposed control system is robust with respect to bounded machine parameter variations and errors on rotor position measurement. In the paper, it is also shown how the proposed current control algorithm can be modified in order to achieve asymptotic active current tracking and zero reactive current stabilization during steady state. An extension for the speed control objective and output EMF control during the excitation–synchronization stage are also presented. Simulation and experimental tests demonstrate high dynamic performance and robustness of the control algorithm for typical operating conditions. The proposed controller is suitable for both energy generation and electrical drive application with restricted speed variation range.

Speed Sensorless Control of Induction Motors Based on a Reduced-Order Adaptive Observer

A novel speed sensorless indirect field-oriented control for the full-order model of the induction motor is presented. It provides local exponential tracking of smooth speed and flux amplitude reference signals together with local exponential field orientation, on the basis of stator current measurements only and under assumption of unknown constant load torque. Speed estimation is performed through a reduced-order adaptive observer based on the torque current dynamics, while no flux estimate is required for both observation and control purposes. The absence of the flux model in the proposed algorithm allows for simple and effective time-scale separation between the speed-flux tracking error dynamics (slow subsystem) and the estimation error dynamics (fast subsystem). This property is exploited to obtain a high performance sensorless controller, with features similar to those of standard field-oriented induction motor drives. Moreover, time-scale separation and physically-based decomposition into speed and flux subsystems allow for a simple and constructive tuning procedure. The theoretical analysis based on the singular perturbation method enlightens that a persistency of excitation condition is necessary for the asymptotic stability. From a practical viewpoint, it is related to the well-known observability and instability issues due to a lack of back-emf signal at zero-frequency excitation. A flux reference selection strategy has been developed to guarantee Persistency of excitation in every operating condition. Extensive simulation and experimental tests confirm the effectiveness of the proposed approach.

Exponentially convergent rotor resistance estimation for induction motors

A new estimation algorithm is presented which provides exponential estimation of rotor resistance for induction motor drives in physical operating conditions. The exponential convergence is not influenced by the value assumed by rotor speed, including zero speed. The algorithm also provides flux estimates and may be viewed as an adaptive observer. Experimental results show good performance with a sampling time of 0.8 ms which makes the algorithm implementable on-line by available digital signal processors. >

Indirect stator flux-oriented output feedback control of a doubly fed induction machine

A new indirect stator flux field-oriented output feedback control for doubly fed induction machine is presented. It assures global exponential torque tracking and stabilization of the stator-side power factor at unity level, provided that electric machine physical constraints are satisfied. Based on the inner torque control system, a speed tracking controller, with load torque compensation is designed using passivity approach. In contrast to existing solutions, the stator voltage vector oriented reference frame is adopted in order to improve robustness properties with respect to induction machine parameters variation. To achieve smooth connection of electric machine to the line grid a synchronization algorithm is developed for excitation stage of the doubly fed induction machine operation. The solution proposed requires measurements of line voltages, rotor currents, rotor position and speed. Intensive experimental studies demonstrate high dynamic performance capabilities of the control algorithm proposed.

Adaptive output feedback control of current-fed induction motors with uncertain rotor resistance and load torque

We present an adaptive nonlinear control algorithm for current-fed induction motors which is adaptive with respect to both load torque and rotor resistance. The eighth-order adaptive controller provides reference signals for stator currents on the basis of: measurements of rotor speed, stator currents and stator voltages; estimates of rotor fluxes, which are the unmeasured state variables; estimates of torque load and rotor resistance which may vary considerably during operations. The dynamic controller guarantees speed tracking and bounded signals for every initial condition of the motor. When persistency of excitation conditions are satisfied, the rotor flux tracking error tends asymptotically to zero so that motor power efficiency may be improved. Moreover, in this case, the estimates of rotor fluxes, torque load and rotor resistance tend asymptotically to their true values. Simulations show that persistency of excitation conditions are satisfied in physical operating conditions and that all estimation errors tend quickly to zero so that high tracking performances are achieved both for speed and rotor flux.