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SUMMARYThis paper investigates the problem of adaptive control for networked control systems with unknown model parameters and randomly missing outputs. In particular, for a system with the autoregressive model with exogenous input placed in a network environment, the randomly missing output feature is modeled as a Bernoulli process. Then, an output estimator is designed to online estimate the missing output measurements, and further a Kalman filter-based method is proposed for parameter estimation. Based on the estimated output and the available output, and the estimated model parameters, an adaptive control is designed to make the output track the desired signal. Convergence properties of the proposed algorithms are analyzed in detail. Simulation examples illustrate the effectiveness of the proposed method.

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Different proportions of nanoscale TiO 2 (nano-TiO 2 )-filled polybutylene succinate (PBS) composites were prepared by vane extruder. The crystalline, thermal, dynamic viscoelastic, mechanical, and UV-resistance properties of the composites were studied, and X-ray diffraction, differential scanning calorimetry, and thermogravimetric analysis were conducted. Results show that the crystalline structure of the PBS composites did not change with TiO 2 addition. TiO 2 almost has no effect on the crystallization and melting behavior of PBS. Nevertheless, the introduction of TiO 2 has improved the thermal stability, tensile modulus, flexural modulus, and flexural strength of the PBS composites. The UV resistance of the composites has also been significantly enhanced with TiO 2 addition. POLYM. COMPOS., 35:53-59, 2014.

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This paper devotes to the image compression and encryption problems. We develop a novel hybrid scheme based on block compressive sensing. Concentrate on taking full advantage of the different frequency coefficients sparsity, the nonuniform sampling strategy is adopted to improve the compression efficiency. First, the discrete cosine transform coefficients matrices of blocks are transformed into vectors by zigzag scanning. The different frequency components are extracted in the front, middle, and back of vectors, respectively. Using the measurement matrices with different dimensions, the combination of lowand high-frequency components, together with the medium-frequency coefficients are compressed simultaneously. Second, the recombinational block measurements are re-encrypted by the permutation-diffusion framework. The logistic map is introduced for key stream generation. In order to accomplish a sensitive and effective cryptosystem, the control strategy for secret keys is employed. The simulation results indicate that the proposed scheme forms a high balance between reconstruction performance, storage and computational complexity, and hardware implementation. Moreover, the security analyses demonstrate the satisfactory performance and effectiveness of the proposed cryptosystem. The scheme can work efficiently in the parallel computing environment, especially for the images with medium and large size. INDEX TERMS Block compressive sensing, image cryptosystem, logistic map, nonuniform sampling strategy.