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Abstract

Geomechnical model testing has been widely applied as a kind of research technique in underground engineering problems. However, during the practical application process, due to the influence of many factors, the desired results cannot be obtained. In order to solve this problem, based on the measurement requirements of the model test, combined with FBG(Fiber Bragg Grating) sensor technology and traditional measurement methods, an FBG monitoring system, Micro-multi-point displacement test system, resistance strain test system and surrounding rock pressure monitoring system are developed. Applying the systems to a model test of the tunnel construction process, the displacement in advance laws of tunnel face, radial displacement distribution laws and surrounding rock pressure laws are obtained. Test results show that a multivariate information monitoring system has the advantage of high precision, stability and strong anti-jamming capability. It lays a solid foundation for the real-time data monitoring of the tunnel construction process model test.
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Abstract

An on-line optimising control strategy involving a two level extended Kalman filter (EKF) for dynamic model identification and a functional conjugate gradient method for determining optimal operating condition is proposed and applied to a biochemical reactor. The optimiser incorporates the identified model and determines the optimal operating condition while maximising the process performance. This strategy is computationally advantageous as it involves separate estimation of states and process parameters in reduced dimensions. In addition to assisting on-line dynamic optimisation, the estimated time varying uncertain process parameter information can also be useful for continuous monitoring of the process. This strategy ensures that the biochemical reactor is operated at the optimal operation while taking care of the disturbances that are encountered during operation. The simulation results demonstrate the usefulness of the two level EKF assisted dynamic optimizer for on-line optimising control of uncertain nonlinear biochemical systems.
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