This paper proposes an intelligent technique by combining multilayer feed-forward neural networks (MLFNN) and beetle antennae search (BAS) algorithm for the inverse calibration of a 7R manipulator. First of all, the MLFNN is optimized by BAS. Then, the optimized BAS-MLFNN method is employed for the nonlinear mapping from the true angles of the joint to the errors of the joint. The true angle values of the joints are selected as the inputs and the joint errors as the outputs. The simulation of calibration is implemented on a Kuka’s LWR manipulator. Numerical simulation results show that compared with the commonly used BPNN, the proposed BAS-MLFNN method possesses better performance in terms of higher precision.

This paper proposes an improved optimal adaptive control algorithm to accelerate convergence for sine control of general multichannel coupled system, as well as enhance the stability. First of all, the convergence of traditional multi-input multi-output (MIMO) sine control method is analytically investigated in the presence of frequency response function (FRF) error. Then, the controller with the improved optimal adaptive control algorithm is developed, where a high-precision algorithm for amplitude and phase estimation is proposed to guarantee the accuracy of the response vector calculation. Numerical simulation results show that the proposed method possess excellent performance with fast convergence rate and strong robustness.

The seismic simulating shaking table is a typical electro-hydraulic servo test system and is controlled by a servo valve. The test system is widely used in the structural anti-seismic test. The seismic simulating shaking table usually has a low frequency response and a low damping which greatly limit its application for the wide bandwidth test. To further expand the bandwidth of the seismic simulating shaking table and increase its damping TVC (three-variable control) algorithm is proposed. In this paper, we research the TVC (three-variable control) algorithm for the seismic simulating shaking table, and also analyze its correction actions on the system characteristics of the shaking table achieved by both the TVC feedback and TVC feedforward loops. Then we further verify the improvement effects on the system’s frequency response characteristics of the shaking table taken by the TVC algorithm. The algorithm can expand the system bandwidth by introducing a velocity feedback and can increase the system damping by introducing an acceleration feedback. The TVC feedforward loop can eliminate the system poles near to the imaginary axis of system’s closed-loop transfer function and can also further expand the system bandwidth. Finally, we conduct two types of tests on a seismic simulating shaking table: sine sweep tests and seismic waveform replication tests. The results of the sine sweep tests show that the TVC algorithm can effectively improve the system’s frequency response characteristics of the shaking table and also improve its response speed. And the results of the seismic waveform replication tests show that the TVC algorithm can improve the replication accuracy of the seismic waveform.

Three-parameter control strategy, which incorporates signals of displacement, velocity and acceleration coming from the tested subject, has become a major technology in servo control for seismic simulation shaking table. The three-parameter control strategy allows the system to broaden its response bandwidth and increase its damping property. Normally, trial and error method is used to determine the proper value of each parameter, so the tested system can exhibit favorable frequency response performances. Whereas it can be very labor-intensive to find the optimal parameter values during the parameter trial and error process which also has a certain possibility to fail. To solve this problem, a novel rapid parameter tuning method of three-parameter control strategy has been proposed to consume less time in calculation, but realize the optimal response characteristics at the same time. The servo controller for seismic simulation shaking table is usually made up of three-parameter feedback, feed forward links and signal generator. By deducing the transfer function for each feedback and feed forward link the values of three parameters for the servo controller can be tuned efficiently. Simulation and experiment results have shown the control results of the novel and traditional three-parameter control methods to be virtually identical, proving the feasibility and validity of this novel parameter tuning method proposed in this study. Moreover, this method is proven to have a wide application in different tested system with different vibration characteristics, and it won’t bereave the system of its initial stability.