摘要
A novel nonlinear control algorithm based on hybrid neural networks ispresented to cope with the high-accuracy synchronization control problem for a dual-actuatorelectrohydraulic drive system which plays an important role for the development of elastomericlaunchers. A new objective function for better synchronization performance is introduced and alearning algorithm to adjust the weights of the neural network, based on the gradient descentalgorithm, is also derived. The hybrid neural network control algorithm guarantees high-accuracysynchronization performance of two motion cylinders and fast dynamic response as well as goodstability of the control system. Prototype test results on the dual-actuator electrohydraulic drivesystem verifys the effectiveness of the proposed approach.
A novel nonlinear control algorithm based on hybrid neural networks ispresented to cope with the high-accuracy synchronization control problem for a dual-actuatorelectrohydraulic drive system which plays an important role for the development of elastomericlaunchers. A new objective function for better synchronization performance is introduced and alearning algorithm to adjust the weights of the neural network, based on the gradient descentalgorithm, is also derived. The hybrid neural network control algorithm guarantees high-accuracysynchronization performance of two motion cylinders and fast dynamic response as well as goodstability of the control system. Prototype test results on the dual-actuator electrohydraulic drivesystem verifys the effectiveness of the proposed approach.
