In this paper, the design and implementation of adaptive speed controller for a sensorless synchronous reluctance motor (SynRM) drive system is proposed. A combination of well-known adaptive input-output feedback linearization (AIOFL) and adaptive backstepping (ABS) techniques are used for speed tracking control of SynRM. The AIOFL controller is capable of estimating motor two-axis inductances ...

The paper presents a certainty equivalence output feedback backstepping adaptive control design method for the systems of any relative degree with unmatched uncertainties without over-parametrization. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system’s input and output tracking errors can be systematically...

this paper works on the concept of flatness and its practical application for the design of an optimal transient controller in a synchronous machine. the feedback linearization scheme of interest requires the generation of a flat output from which the feedback control law can easily be designed. thus the computation of the flat output for reduced order model of the synchronous machine with simp...

 An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...

Solutions exist for the problem of canceling sinusoidal disturbances by the measurement of the state or by the measurement of an output for linear and nonlinear systems. In this paper, an adaptive backstepping controller is designed to cancel sinusoidal disturbances forcing an unknown linear time-invariant system in controllable canonical form which is augmented by a linear input subsystem with...

Black-box modeling techniques based on artificial neural networks are opening new horizons for modeling and controlling nonlinear processes in biotechnology and chemical process industries. The link between dynamic process models and actual process control is provided by the concept of model based control (MBC), e.g. Internal Model Control (IMC) or Model Based Predictive Control (MBPC). To avoi...

The robust H∞ control problem for the generator excitation system with the damping coefficient uncertainty and external disturbances, is addressed. Storage functions of the control system are constructed based on modified adaptive backstepping sliding mode control method and Lyapunov method. A nonlinear robust H∞ controller and a parameter updating law are obtained simultaneously. The controlle...

In this paper, an adaptive fuzzy backstepping output feedback control approach is proposed for a class of strict-feedback stochastic nonlinear systems with time delays and immeasurable states. Fuzzy logic systems are firstly utilized to approximate the unknown nonlinear functions, and then a fuzzy state observer is designed to estimate the immeasurable states. By combining the fuzzy adaptive co...

This paper presents neural adaptive control methods for a class of nonlinear systems in the presence of actuator saturation. Backstepping technique is widely used for the control of nonlinear systems. By introducing alternative state variables and implementing state transformation, the system can be reformulated as output feedback of a canonical system, which ensures that the controllers can be...