This work proposes a finite-horizon servo state-dependent Riccati equation (SDRE) to control two classes of aerospace systems. The SDRE is widely used for nonlinear and optimal control of different systems in theory and practice. In this work, an augmented integrator was added to the SDRE (servo SDRE) to increase performance of the controller, especially to decrease steady-state error. The finite-horizon structure developed for servo SDRE features the advantages of both methods. Attitude control of super-maneuverable aircraft was modeled and simulated. It was then compared with a conventional SDRE controller to show the advantages of the proposed combination. A magnetically suspended double-gimbal control moment gyroscope was tested using the finite-horizon servo SDRE because the control moment gyroscope is the primary attitude control actuator for spacecraft. The results showed that the servo structure improved the performance and decreased the error of the SDRE using a simple systematic approach. The finite-horizon option completes the task sooner than common controllers.
This paper presents the design process and controlling method for a four-cylinder electro-hydraulic (EH) system. The main contribution of this system is regarding it as a mechatronic plant which includes controller, actuating mechanism, position sensor. In addition the integrated system must be controlled precisely. The control scheme used on this plant is a hybrid controller. It consists of a PID MIMO and a sliding mode controller. Moreover a fuzzy logic base algorithm is applied in order to sustain the synchronization. The performance and accuracy of the control strategy in the presence of parametric uncertainties is confirmed through simulations.
This work addresses an autonomous underwater vehicle (AUV) for applying nonlinear control which is capable of disturbance rejection via intelligent estimation of uncertainties. Adaptive radial basis function neural network (RBF NN) controller is proposed to approximate unknown nonlinear dynamics. The problem of designing an adaptive RBF NN controller was augmented with sliding mode robust term to improve trajectory tracking and regulation in presence of uncertainties. Moreover, stability proof of proposed control scheme was shown with Lyapunov theory. Furthermore, the control, design and simulation results are provided without any simplification of the entire system. Although the design approach of this paper is implemented on REMUS this point of view can be applied on any AUV using the same technique.
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