An improved particle swarm optimization (PSO) with adaptive weighted delay velocity (PSO-AWDV) is proposed in this paper. A new scheme blending weighted delay velocity is firstly presented for a new PSO with weighted delay velocity (PSO-WDV) algorithm. Then, to adaptively update the velocity inertia weight, an adaptive PSO-AWDV algorithm is developed based on the evolutionary state of the particle swarm evaluated via a new estimation method. The newly proposed adaptive PSO-AWDV algorithm is tested based on some famous benchmark functions, which can confirm that the performance of PSO-AWDV is superior to several well-known PSO variants and intelligent optimization algorithms in literature.

In this study, we propose a novel 2D lag-complex logistic map (LCLM). The 2D-LCLM is derived from the conventional 2D logistic map by extending its variables from real numbers to complex field. The bifurcation diagrams, Lyapunov exponents, and the evolution of chaotic attractors have been exploited for evaluating the chaotic behavior. Results show that the 2D-LCLM has extensive chaotic intervals, good ergodicity, and unpredictable trajectories. For further studying its practical significance, we then construct a color image cryptosystem based on 2D-LCLM. Bit-level permutation and one-time keys are used for speeding up the computational speed and defending chosen plaintext attack. Simulation results and corresponding analysis reveal that the cryptosystem has large key-space and good key sensitivity, and its information entropy approaches to the ideal value. Hence, the cryptosystem based on 2D-LCLM can strongly resist traditional cipher attacks.

Smooth path planning is very important to mobile robots with continuous-curvature constraint, but there are still some limitations and drawbacks on traditional planning approach. To deal with this problem, a new approach combined with parametric cubic Bezier curve (PCBC) and particle swarm optimization with adaptive delayed velocity (PSO-ADV), is developed to plan the smooth path of mobile robots. Unlike the traditional smooth path consisting of several linear and curve segments with discontinuous curvature at the joints, the smooth path composed of PCBC segments has equivalent curvature at the segment joints, thereby it is able to attain continuous curvature along the whole smooth path. In terms of the mathematical formulation of PCBC, the smooth path planning is essentially an optimization problem to seek the optimal control points and parameters of PCBC segments. To handle this intractable problem and some frequently encountered troubles (e.g. premature convergence and local trapping), a new PSO-ADV algorithm is developed by blending the term of adaptive delayed velocity, and its superiority can be confirmed by several simulation experiments. The new approach is finally applied to produce the smooth path with continuous-curvature constraint, and can achieve superior performance in comparison with traditional method.

Tunable polarization-nonsensitive electromagnetically induced transparency (EIT) based on Dirac semimetal films (DSF) at terahertz frequencies is numerically studied in this paper. We first numerically investigate the EIT effect in a DSF-based terahertz metamaterial structure comprising a DSF strip and two DSF L-shaped resonators. To achieve the polarization-nonsensitive EIT effect, we introduce one vertical strip and two more L-shaped resonators to the above structure. The transmission spectra of the new structure show strong polarization-nonsensitive characteristic because of the fourfold symmetry. By analyzing the surface currents and electric field distribution at the resonant frequencies, we demonstrate that an EIT effect arises from the bright–bright mode coupling. Moreover, the polarization-nonsensitive EIT structure exhibits a blue shift with the increase in the Fermi energy of the DSF without having to re-optimize its geometrical parameters. Our study opens a new path for developing terahertz devices such as terahertz switches.

The development of accurate data-driven models is of great significance for online monitoring and control of industrial processes. In this study, a nonlinear dynamic soft-sensing algorithm for measuring and predicting the nitrogen oxides (NOx) emissions of the denitration system of a power plant was developed. First, the processes and principles of the denitration system were studied. Second, a soft-sensing algorithm based on long short-term memory (LSTM) and least absolute shrinkage and selection operator (LASSO) was proposed. The dynamics of the process were captured by LSTM, and the selection of influential input variables was achieved by LASSO. A moving window cross validation (MWCV) strategy was applied to determine the hyperparameters of the proposed algorithm. Third, the proposed algorithm was implemented to predict NOx emissions from a denitration system. The experimental results demonstrated that the proposed approach had superior accuracy and higher precision of variable selection compared with other state-of-the-art soft-sensing algorithms. In addition, the variable importance analysis provided by the proposed algorithm is consistent with the principles of chemical reactions and field experiences. The proposed algorithm could provide theoretical and technical support for the optimization of the denitration system and predictive control design of the denitration process.

To efficiently inspect surface defects on steel ball bearings, a new method based on a circumferential eddy current array (CECA) sensor was proposed here. The best probe configuration, in terms of the coil quality factor (Q-factor), magnetic field intensity, and induced eddy current density on the surface of a sample steel ball, was determined using 3-, 4-, 5-, and 6-coil probes, for analysis and comparison. The optimal lift-off from the measured steel ball, the number of probe coils, and the frequency of excitation current suitable for steel ball inspection were obtained. Using the resulting CECA sensor to inspect 46,126 steel balls showed a miss rate of ~0.02%. The sensor was inspected for surface defects as small as 0.05 mm in width and 0.1 mm in depth.