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Earthquakes are one of the most frequent and inevitable natural disasters that occur on Earth. The most important seismic isolation device used in the isolation technology is the isolation bearing, but the limited structure of the isolation bearing is not suitable for the seismic isolation and shock absorption of smart transportation buildings. Therefore, it is very important to improve the new generation of seismic isolation structures with good seismic isolation effect, stable performance, and economical performance. It is very important to study the structural composition of the isolation bearing and the rigidity of the isolation structure. Isolation bearings are designed to resist and absorb the energy of seismic shocks by installing substructures in the structure. Active control involves installing sensors on the structure and its foundation to determine how the structure responds to seismic action. In this paper, based on the intelligent transportation of the sensor network, the reticulated shell structure of the isolation bearing is analyzed. By introducing the architecture and network layout of the sensor network, it is beneficial to obtain more accurate seismic data in complex and difficult terrain. This paper analyzes the technical principle of seismic isolation technology, which can effectively avoid the upward transmission of ground vibration by increasing the flexibility and proper damping of the system. From the experimental data of the seismic response of the ground-isolated structure to the near-field pulsation and far-field vibration, the total energy of the ground-isolated structure under the near-field pulsed ground motion is the largest. The seismic isolation effect of the reticulated shell structure of the seismic isolation bearing prevents more than 80% of the seismic energy from being transmitted to the superstructure. [ABSTRACT FROM AUTHOR]

The cruise control of high-speed trains is challenging due to the presence of time-varying air resistance coefficients and control constrains. Because the resistance coefficients for high-speed trains are not accurately known and will change with the actual operating environment, the precision of high speed train model is lower. In order to ensure the safe and effective operation of the train, the operating conditions of the train must meet the safety constraints. The most traditional cruise control methods are PID control, model predictive control, and so on, in which the high-speed train model is identified offline. However, the traditional methods typically suffer from performance degradations in the presence of time-varying resistance coefficients. In this paper, an adaptive model predictive control (MPC) method is proposed for cruise control of high-speed trains with time-varying resistance coefficients. The adaptive MPC is designed by combining an adaptive updating law for estimated parameters and a multiply constrained MPC for the estimated system. It is proved theoretically that, with the proposed adaptive MPC, the high-speed trains track the desired speed with ultimately bounded tracking errors, while the estimated parameters are bounded and the relative spring displacement between the two neighboring cars is stable at the equilibrium state. Simulations results validate that proposed method is better than the traditional model predictive control. [ABSTRACT FROM AUTHOR]

It is a challenge to maintain a safe and efficient tracking for multiple high-speed trains under the moving block operational mode. In this paper, a novel cooperative tracking control based on a consensus algorithm and artificial potential field theory is proposed to realize the train tracking within a distance range. A tunable artificial potential function is first designed to dynamically adjust the distance between adjacent high-speed trains with real-time train states. By regulating the parameters of the artificial potential function, the safety distance can be adjusted according to the required tolerance deviation of the actual distance. Under the proposed strategy, each high-speed train operates with the desired speed and tracks the preceding one with an adjustable distance range. Numerical train operational cases are investigated to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]