The displacement tracking performance of the electro-hydraulic servo actuator is critical for hydraulic active suspension control. To tackle the problem of slow time-varying parameters in the existing actuator dynamics model, a nonlinear adaptive back-stepping control (ABC) approach is adopted. Simultaneously, the parameters of the nonlinear ABC are difficult to configure, resulting in a poor control effect. An enhanced particle swarm optimization (PSO) approach integrating crazy particles (CP) and time-varying acceleration coefficients (TVAC) is suggested to optimize the controller settings. Furthermore, in order to obtain satisfactory dynamic characteristics of the transition process, the absolute value of the error time integral performance index is used as the minimum performance index function of parameter selection, and the square term of the control input is added to the performance index function to prevent excessive controller energy. Finally, it can be observed from the simulation results of the highest value emax of the displacement tracking error, the average value eμ of error, and the standard deviation eσ of error that the performance of the ABC parameters optimized by PSO+CP+ATVC is superior to the manually given ABC parameters. Therefore, this control method significantly improves the stability and speed of the control system. It provides a new research idea for the parameter optimization of controllers.
An online neural-net control system, in which learning and control are independently carried out, is proposed for the problem of ship motion control, including roll, yaw and sway stabilization at the same time. Disturbance models, including roll moment, yaw moment and sway force induced by sea wave and wind, are presented by the experimental data in tank. With the three disturbance models as inputs, a recurrent neural network is proposed to approach the forward model of the real ship, and the real time recurrent learning algorithm is described to train the forward model. Then neural-net controller is presented to reduce the roll, yaw and sway synthetically. This paper proposes the adaptation process of control system and applies it to the ship HD702. The approaching accuracy of forward model network and the synthetic control effect of the three motions are investigated.
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