The control of large scale dynamical systems is one of the biggest challenges facing control
engineers today. Large scale systems are common in applications such as chemical …

An adaptive learning control scheme is presented for uncertain robotic systems that is
capable of tracking the entire profile of the reference input. The control scheme consists of …

This dissertation focuses on the high performance robust control of nonlinear systems in the
presence of parametric uncertainties and uncertain nonlinearities (eg, disturbances) and its …

An adaptive, sliding control algorithm is developed for automated throttle control of an IC
engine to be used in drive-by-wire applications such as coordinated engine/transmission …

A" learning system" possesses the capability to improve its performance over time by
interacting with its environment. A learning control system is designed so that its" learning …

A redesign of model reference adaptive control using a non-quadratic Lyapunov function for
deriving a new adaptive law leads to a tracking error e (t) belonging to the L 1+ α signal …

The highly nonlinear mature of the generator and system behaviour following a severe
disturbance precludes the use of classical linear control techniques. In this paper, a …

We present an adaptive, partial-state feedback, position tracking controller for the full-order,
nonlinear dynamic model representing an induction motor actuating a mechanical …

We propose a robust model reference tracking control design for non-holonomic mechanical
systems under parametric perturbation and external disturbance. A design procedure with …

A modular approach to adaptive control of nonlinear systems introduced previously is
presented in a general framework. This approach abandons the certainty equivalence …