In this paper, an adaptive optimizing control is proposed for nonlinear synchronous generator system with uncertain disturbance. Considering the issue of uncertain item, a low-order Extended State Observer (ESO) is constructed to track each order states. en, combining Backstepping technology and proposed ESO, a dynamic compensation control is designed to compensate the uncertainty disturbance in each state quantity. e proposed method demonstrated that stability of the system can be ensured, and tracking burden of ESO can be reduced. Finally, simulation results can show a good tracking performance and anti-interference ability by the proposed control method.
In this paper, the 3D measurement of the hull plate is used as the background. It analyzes the principle of laser three-dimensional scanning. The independent k-neighbor problem is considered to improve the method of law loss propagation adjustment, at point cloud data segmentation. It improves the K-neighbor point cloud data boundary feature extraction algorithm. A point cloud reduction algorithm based on K-d tree space partitioning and local curvature threshold is proposed, and the algorithm flow is given. Finally, the related algorithms are simulated and tested, and the results also verify the feasibility of the above method , meet the needs of hull plate measurement.
In practical robot control systems, the input constraints problem, caused by a limited actuator output amplitude, is due to its own physical characteristics. In traditional control methods, this nonlinear problem is not paid enough attention, especially for robot systems with unknown disturbance. To handle this problem, adaptive compensate control for uncertain robot system with input constraints is proposed. It is combined with adaptive compensate control and hyperbolic tangent function to ensure that the uncertain robot system with input constraints is stable. The simulation results showed that the proposed method can make the uncertain robot system reach a stable state.
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