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Iterative learning control demands the same initial state in each iteration, which is equal to the desired state. But this condition is unattainable in practice. This paper addresses the problem of some fixed initial state in iterative learning control for high-order nonlinear system. It presents a new control algorithm. In the process of tracking, this algorithm can rectify the initial errors through...
In this work, we focus on the properties of trajectory in discrete-time system, under some conditions, the behavior of this class of systems' trajectory is studied. Using this properties, several characterizations of discrete-time system are also given, which is very helpful to study the ISS property of discrete-time system.
This brief extends the new neuroadaptive control framework for continuous-time nonlinear uncertain dynamical systems based on a Q -modification architecture to discrete-time systems. As in the continuous-time case, the discrete-time update laws involve auxiliary terms, or Q-modification terms, predicated on an estimate of the unknown neural network weights which in turn involve a set of auxiliary...
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