Shaking table testing is a common experimental method in earthquake engineering for performance assessment of structures subjected to dynamic excitations. As most shaking tables are driven by servo hydraulic actuators to meet the potentially significant force stroke demand, the review is restricted to hydraulic shaking tables. The purpose of the control systems of hydraulic shaking tables is to reproduce reference signals with low distortion. Accurate control of actuators is vital to the effectiveness of such apparatus. However, the system dynamics of a shaking table and the specimens to be tested on the shaking table are usually very complex and nonlinear. Achieving the control goal can prove to be challenging. A variety of closed- and open-loop control algorithms has been developed to solve different control problems. With the focus placed on the control schemes for hydraulic shaking tables, the paper reviews algorithms that are currently used in the testing industry, as well as those which are the subject of academic and industrial research. It is by no means a complete survey but provides key reference for further development.

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To improve the magnetorheological (MR) properties and dispersion stability of the carbonyl iron (CI) particles, bidisperse magnetorheological (BMR) fluids consisting of magnetic micron-sized CI and nanoparticles dual-coated with gelatin and multi-walled carbon nanotubes (MWCNTs) were synthesized for the first time. Gelatin was used as a grafting agent to improve the stability of bidisperse magnetic particles and restrict the oxidation of nanoparticles (Fe 3 O 4 ). And a dense network composed of MWCNTs on the surface of gelatin-coated bidisperse particles was fabricated based on the self-assembly of MWCNTs to produce considerably rough surfaces. The influence of functional dual-coated layer on rheological performance such as shear stress and yield stress behavior was investigated by a rotational rheometer upon various magnetic field applications. Additionally, the dispersion stability was measured through sedimentation tests. The results showed that CI-Fe 3 O 4 -Gelatin-MWCNTs (CI-Fe 3 O 4 -G-NT) magnetic microspheres possessed enhanced MR properties compared with those from CI-Fe 3 O 4 -Gelatin (CI-Fe 3 O 4 -G) microspheres, while the dispersion stability of CI-Fe 3 O 4 -G-NT microspheres was still maintained.

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Based on adaptive inverse control theory, combined with neural network, neural network adaptive inverse controller is developed and applied to an electro-hydraulic servo system. The system inverse model identifier is constructed by neural network. The task is accomplished by generating a tracking error between the input command signal and the system response. The weights of the neural network are updated by the error signal in such a way that the error is minimized in the sense of mean square using (LMS) algorithm and the neural network is close to the system inverse model. The above steps make the gain of the serial connection system close to unity, realizing waveform replication function in real-time. To enhance its convergence and robustness, the normalized LMS algorithm is applied. Simulation in which nonlinear dead-zone is considered and experimental results demonstrate that the proposed control scheme is capable of tracking desired signals with high accuracy and it has good real-time performance.

This paper focuses on an electro-hydraulic servo system, which is derived from a shaking table. It proposes a control scheme based on a back propagation (BP) neural network, whose weights are trained by the particle swarm optimization (PSO) according to the fitness, which is determined by the input and the feedback signals. Each particle of PSO includes weights and thresholds of BP. The movement of each particle is adjusted by its local best-known position and the global best-known position in the searching space. With the update, a satisfactory solution can be achieved. In order to show the performance of the proposed control scheme, the designed network is also trained and tested by BP only. The comparisons between the PSO-BP and BP networks demonstrate that the PSO-BP one has better performance than that of BP, both in convergence speed and in convergence accuracy.

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The shaking table is an important experimental apparatus for mechanical environment tests. This work is focused on an electro-hydraulic shaking table, which has a single degree of freedom. Its configuration and working principle are described. A three-variable controller composed of feed-forward and feedback is applied to achieve iso-acceleration control. The acceleration excitation signal is filtered by an input filter to obtain input variables for the three-variable controller. From the sinusoidal shaking results, harmonic distortion exists in the acceleration response. The frequencies of harmonics are integer multiples of the fundamental frequency. Different harmonic distortion and harmonic distribution occur in the acceleration response excited by different acceleration excitation signals. The acceleration harmonic distortion is decreased as the amplitude and frequency of the excitation signal are increased.