Abstract: Based on general proportional integral (GPI) observers and sliding mode control technique, a robust control method is proposed for the master-slave synchronization of chaotic systems in the presence of parameter uncertainty and with partially measurable output signal. By using GPI observer, the master dynamics are reconstructed by the observations from a measurable output under the differential algebraic framework. Driven by the signals provided by GPI observer, a sliding mode control technique is used for the tracking control and synchronization of the master-slave dynamics. The convincing numerical results reveal the proposed method is effective, and successfully accommodate the system uncertainties, disturbances, and noisy corruptions.
Abstract: Reentry trajectory optimization is a multi-constraints
optimal control problem which is hard to solve. To tackle it, we
proposed a new algorithm named CDEN(Constrained Differential
Evolution Newton-Raphson Algorithm) based on Differential Evolution(
DE) and Newton-Raphson.We transform the infinite dimensional
optimal control problem to parameter optimization which is finite
dimensional by discretize control parameter. In order to simplify
the problem, we figure out the control parameter-s scope by process
constraints. To handle constraints, we proposed a parameterless constraints
handle process. Through comprehensive analyze the problem,
we use a new algorithm integrated by DE and Newton-Raphson to
solve it. It is validated by a reentry vehicle X-33, simulation results
indicated that the algorithm is effective and robust.