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This paper proposes a new method of flash qualitative identification (FQI) to qualitatively identify a certain target component from a mixture within half a second by disusing the analytical column, which is a time-consuming unit in current chromatography instruments. First, a Noised Spectrum Identification (NSI) model was constructed for the data set generated directly by diode array detector (DAD) without the process in an analytical column. Then, a method called vector error algorithm (VEA) was proposed to generate an error according to the DAD data set for a mixture and a specific spectrum for the target component to be identified. A criterion based on the error generated by the VEA is used to give a judgement of whether the specific spectrum exists in the DAD data set. Several simulations demonstrate the high performance of the FQI method, and an experiment for three known materials was carried out to validate the effectiveness of this method. The results show that the NSI model concurs with the real experiment result; therefore, the error generated by the VEA was an effective criterion to identify a specific component qualitatively, and the FQI method could finish the identification task within half a second., CHROMATOGRAPHY has been developed as a set of laboratory techniques that are widely applied in the quality control (QC) of mixtures such as herbal medicine, grape wine, petroleum, judicial expertise, [...]

An H∞ iterative learning controller is designed for networked systems with intermittent measurements and iteration-varying disturbances. By modeling the measurement dropout as a stochastic variable satisfying the Bernoulli random binary distribution, the design can be transformed into H∞ control of a 2D stochastic system described by Roesser model. A sufficient condition for mean-square asymptotic stability and H∞ disturbance attenuation performance for such 2D stochastic system is established by means of linear matrix inequality (LMI) technique, and formulas can be given for the control law design simultaneously. A numerical example is given to illustrate the effectiveness of the proposed results.

The problem of H∞ control for network-based 2D systems with missing measurements is considered. A stochastic variable satisfying the Bernoulli random binary distribution is utilized to characterize the missing measurements. Our attention is focused on the design of a state feedback controller such that the closed-loop 2D stochastic system is mean-square asymptotic stability and has an H∞ disturbance attenuation performance. A sufficient condition is established by means of linear matrix inequalities (LMIs) technique, and formulas can be given for the control law design. The result is also extended to more general cases where the system matrices contain uncertain parameters. Numerical examples are also given to illustrate the effectiveness of proposed approach.

In order to solve the problem of power exchange between areas of multi-area power systems under the power market, this paper designs a power trading contract based on the generation participation matrix, so as to simulate the specific process of power change in each area. With the integration of wind power into the large-scale power system, it is difficult to model the multi-area power system. For this situation, this paper designs a data-driven model-free adaptive load frequency control algorithm based on collecting input and output data, which gets rid of the dependence of the power system on the model. Along with the frequent transmission of input and output data in each area, the communication load of the power system also increases. Aiming at saving communication resources, this paper designs an event-triggered mechanism to reduce the communication bandwidth. The stability of the control algorithm is demonstrated theoretically. Finally, a three-area power system with wind penetration is used as an example to simulate and verify the effectiveness of the proposed algorithm in this paper. [ABSTRACT FROM AUTHOR]

The event-triggered model-free adaptive control problem for a class of multiple input and multiple output (MIMO) nonlinear system under denial of service (DoS) attacks is investigated in this paper. To economize the limited bandwidth resources, an event-triggered mechanism is designed between the sensor and controller. First, intermittent denial of service attack is modeled, which is described as limited by frequency and duration, without more specific assumptions about the structure of attacks strategies. Then, with the help of the dynamic linearization method, a novel event-triggered model-free adaptive control algorithm is designed. The predictive output increments in the algorithm are used to compensate for the influence of DoS attacks on the system. Subsequently, the stability of the system is analyzed by using the Lyapunov method to determine the convergence of the tracking error. Finally, two simulation examples illustrate the validity of the design. [ABSTRACT FROM AUTHOR]