Entity

Time filter

Source Type


Lv R.-Q.,Northeastern University China | Zhao Y.,Northeastern University China | Zhao Y.,The State Key Laboratory of Synthetical Automation for Process Industries | Liu M.-C.,Northeastern University China
Instrumentation Science and Technology | Year: 2016

The combination of fiber-loop ring-down spectroscopy and a long-period fiber grating were employed in an intensity-interrogated refractive index sensing method using a broad band light source and the specifically designed long-period fiber grating. Compared with the traditional long-period-fiber-grating based refractive index sensors, this approach monitored the decay of the optical signal passing through the loop of the long fiber grating. The decay time changed regularly when the grating was immersed in surrounding media with varying refractive indices. This instrumentation offered reduced cost and eliminated the influence of source fluctuation. The sensitivity and resolution were 2421 ns/RIU and 3 × 10−4 for refractive index values from 1.3330–1.3737. 2016 Copyright © Taylor & Francis Group, LLC


Liu L.,Northeastern University China | Liu L.,The State Key Laboratory of Synthetical Automation for Process Industries | Wang Z.,Northeastern University China | Wang Z.,The State Key Laboratory of Synthetical Automation for Process Industries | And 2 more authors.
Neurocomputing | Year: 2015

This paper investigates the adaptive actuator fault compensation control for a class of uncertain multi-input single-out discrete-time systems with triangular forms. The considered actuator faults contain both loss of effectiveness and lock-in-place. With the help of radial basis function neural networks to approximate the unknown nonlinear functions, an adaptive fault tolerant control scheme is designed. Compared with some existing methods, one of features of the proposed method is that we introduce the backstepping technique to achieve the fault-tolerant control task. It is proved that the proposed control approach can guarantee that all the signals of the closed-loop systems are uniformly ultimately bounded and that the output can track a reference signal in the presence of the actuator faults. Finally, three simulation results are provided to confirm the effectiveness of the fault-tolerant control approach. © 2014 Elsevier B.V.


Liu L.,Northeastern University China | Liu L.,The State Key Laboratory of Synthetical Automation for Process Industries | Wang Z.,Northeastern University China | Wang Z.,The State Key Laboratory of Synthetical Automation for Process Industries | And 2 more authors.
Nonlinear Dynamics | Year: 2016

In this paper, we are concerned with the problem of adaptive dynamic surface error constrained control for a class of nonlinear multiple-input-multiple-output systems with unknown backlash-like hysteresis nonlinearities. By transforming the tracking errors into new virtual error variables which are incorporated into the proposed prescribed performance control strategy, the prescribed steady-state and transient performance can be ensured. Compared with the existing methods, we introduce the prediction error which is generated between the system state and the serial–parallel estimation model to construct the adaptive laws for neural network weights. The proposed prediction error technique can be used to compensate the tracking error, which implies that a higher accuracy of the identified neural network model is achieved. It is shown that the proposed control approach can guarantee that all the signals of the resulting closed-loop systems are bounded and the output tracks the desired trajectory, while the tracking error are confined all times within the prescribed bounds. Finally, a simulation example is provided to confirm the effectiveness of the proposed approach. © 2016 Springer Science+Business Media Dordrecht

Discover hidden collaborations