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In order to improve the control performance of the valve-controlled asymmetric cylinder system with negative overlap, it is proposed that the complex nonlinear system is transformed into a linear system based on the neural network inverse system. The structure of the inverse system is been constructed by the state model of the system, and optimised by adding state parameter feedback. So the pseudo-linear system is reduced to second order. An improved back-propagation neural network based on a genetic algorithm is used to solve the inverse model. Aiming at the problem of negative overlap of servo valves and laminar and turbulent flow, the sectional inverse system switched by reference speed is established to improve the accuracy of the inverse system model. For pseudo-linear systems, an internal model controller is designed to improve the control performance of the composite system. The proportion–integration–differentiation and the internal model control (IMC) of the sectional inverse system are compared with that of AMESIM and Simulink joint platform. The results show that the system controlled by the IMC of the sectional inverse system has better response performance, eliminates the asymmetric characteristics in extending and retracting motion response and is less affected by load fluctuation.

There are mechanical coupling interference and hydraulic coupling interference in the vehicle wheel bridge simulation loading system based on secondary regulation, which can cause the control accuracy of the system to decrease obviously and seriously affect the control performance of the system. In order to eliminate the coupling interference between systems, two decoupling methods are proposed, one way to do this is to join the decoupling element, and the other is to join the robust compensator. The simulation results show that the decoupling control of decoupling element has a good decoupling effect on mechanical coupling, but it has no effect on hydraulic coupling. Robust decoupling control has a good decoupling effect on mechanical coupling and hydraulic coupling.

This study concerns adaptive feedforward and hybrid (combined feedback and feedforward) control systems for active vibration suppression of smart flexible beam with a tip mass. By analysing traditional feedforward filtered-X least mean square (FXLMS) algorithm and filtered-X variable step size least mean square (FX-VSSLMS) algorithm, a new hybrid FX-VSSLMS algorithm is developed to improve the control performance of feedforward controllers. A stainless steel beam with a tip mass is employed to simulate flexible robot arm with varying loads. Piezoelectric actuators and sensors are attached to the surface of the beam. Comparison experiments show the effectiveness and benefits of the proposed hybrid FX-VSSLMS method.

With the development of photovoltaic power generation technology, a large number of micro-power grid with distributed generation system have appeared in remote areas. It has the longer transmission line between the traditional power grid and the inverter of the distributed generation system. This caused the equivalent network impedance would be increased and would weak the power-grid characteristics. When the photovoltaic inverter is connected to a weaker power grid, the bandwidth of the control system of the inverter will be reduced. Using the traditional PR control to solve the problem is not ideal. This paper proposes fuzzy quasi-PRD control to improve the current quality. The inverter with the LCL filter has the peak of the resonance oscillation, it will affect the stability of the system. The paper adopts the adjustable virtual damping to suppress resonance. At last, the idea is verified by MATLAB/Simulink. The results show that the fuzzy quasi-PRD control method has better control performance, and dynamic tracking characteristics.