Switching adaptive controllers to control fractional‐order complex systems with unknown structure and input nonlinearities

This article investigates the chaos control problem for the fractional‐order chaotic systems containing unknown structure and input nonlinearities. Two types of nonlinearity in the control input are considered. In the first case, a general continuous nonlinearity input is supposed in the controller, and in the second case, the unknown dead‐zone input is included. In each case, a proper switching adaptive controller is introduced to stabilize the fractional‐order chaotic system in the presence of unknown parameters and uncertainties. The control methods are designed based on the boundedness property of the chaotic system's states, where, in the proposed methods the nonlinear/linear dynamic terms of the fractional‐order chaotic systems are assumed to be fully unknown. The analytical results of the mentioned techniques are proved by the stability analysis theorem of fractional‐order systems and the adaptive control method. In addition, as an application of the proposed methods, single input adaptive controllers are adopted for control of a class of three‐dimensional nonlinear fractional‐order chaotic systems. And finally, some numerical examples illustrate the correctness of the analytical results. © 2014 Wiley Periodicals, Inc. Complexity 21: 211–223, 2015     

Effect of AMC on fixed‐rate traffic with hard delay constraints in mobile broadband systems

The adaptive modulation and coding (AMC) technique, which has been adopted by advanced mobile telecommunication systems, supports a flexible response to the random radio behaviour. As a result, the attained transmission rate over a wireless link is time varying. Hence, resource demands are not deterministic but fluctuating even for calls with constant bit rate service requirements. Consequently, constant bit rate calls are susceptible to a forced call termination because of insufficient resources not only in a target cell during inter‐cell handoffs but also in a serving cell during radio link deterioration. Furthermore, call blocking and dropping probabilities depend on radio propagation conditions among other factors and therefore they are dissimilar throughout a service area. The latter leads to unfairness problems. We analytically measure the impact of AMC on fixed‐rate service with hard delay constraints such as voice for different signal, mobility and traffic conditions. We consider a reference case (call requests are admitted into the system provided there are enough free resources) and two classes of admission control approaches: traditional (only inter‐cell handoffs are prioritised) and modified (all ongoing calls are prioritised). The reported results reveal conditions for which AMC affects voice call performance and can serve as guidelines on admission control design. Copyright © 2013 John Wiley & Sons, Ltd.     

Sparse LMS/F algorithms with application to adaptive system identification

Standard least mean square/fourth (LMS/F) is a classical adaptive algorithm that combined the advantages of both least mean square (LMS) and least mean fourth (LMF). The advantage of LMS is fast convergence speed while its shortcoming is suboptimal solution in low signal‐to‐noise ratio (SNR) environment. On the contrary, the advantage of LMF algorithm is robust in low SNR while its drawback is slow convergence speed in high SNR case. Many finite impulse response systems are modeled as sparse rather than traditionally dense. To take advantage of system sparsity, different sparse LMS algorithms with l_p‐LMS and l₀‐LMS have been proposed to improve adaptive identification performance. However, sparse LMS algorithms have the same drawback as standard LMS. Different from LMS filter, standard LMS/F filter can achieve better performance. Hence, the aim of this paper is to introduce sparse penalties to the LMS/F algorithm so that it can further improve identification performance. We propose two sparse LMS/F algorithms using two sparse constraints to improve adaptive identification performance. Two experiments are performed to show the effectiveness of the proposed algorithms by computer simulation. In the first experiment, the number of nonzero coefficients is changing, and the proposed algorithms can achieve better mean square deviation performance than sparse LMS algorithms. In the second experiment, the number of nonzero coefficient is fixed, and mean square deviation performance of sparse LMS/F algorithms is still better than that of sparse LMS algorithms. Copyright © 2013 John Wiley & Sons, Ltd.     

RS485通信最优波特率研究

在RS485总线中,主机和从机通常使用固定的波特率进行通信;而在实际应用中,波特率的大小和传输的距离是成反比的,波特率越高传输的距离越短,误码率增加越大。为避免波特率过高通信不可靠的问题,根据硬件波特率自适应的机制,文章采用从机数量来计算最优的波特率的方式进行主从机通信。经过实验验证,可提高RS485通信系统的稳定性。     

基于自适应模糊控制的节能装置研究

针对凹版印刷干燥设备,设计节能装置,该装置利用压缩机换热原理,对余热进行再循环利用。设计自适应模糊PID节能控制系统,完成对压缩机,调功器,变频器的实时控制。利用组态软件完成系统界面设计,人机交互简洁,操作方便。控制算法采用自适应模糊PID控制,依靠数据信息来调整模糊逻辑系统的参数,通过在线计算得到最佳控制器参数,抑制不确定性对系统的影响。将节能装置应用到凹版印刷机,实验数据显示,系统耗能减少,效率得到提高,达到节能目的,证明了节能系统的有效性,具有较强的应用价值。     

二冷配水优化建模与混合自适应PSO算法求解

针对连铸二冷区生产环境复杂且存在着大量水雾干扰的情况,建立了连铸水量优化模型并提出了一种混合的自适应粒子群算法来求解连铸二冷水优化问题。依据冶金过程中的工艺要求建立了二冷水量优化模型,并在经典的PSO算法基础上提出了适合该问题求解了混合自适应PSO算法。由于连铸过程存在着偏微分方程约束,传统的优化方法容易陷入局部最优解,不能达到很好的动态优化效果。研究了粒子群算法,基于种群的多样性,不断的自适应的更新粒子群算法中参数,将禁忌搜索的方法和传统的粒子群算法结合,增强了算法的局部搜索能力和全局寻找全局最优的能力。将该算法应用到连铸二冷水动态优化中,实验结果表面该算法能够快速有效的求解该优化问题。该方法用于连铸二冷水优化是可行的、有效的。     

A posterior error estimates for the nonlinear grating problem with transparent boundary condition

The nonlinear grating problem is modeled by Maxwell's equations with transparent boundary conditions. The nonlocal boundary operators are truncated by taking sufficiently many terms in the corresponding expansions. A finite element method with the truncation operators is developed for solving the nonlinear grating problem. The two posterior error estimates are established. The a posterior error estimate consists of two parts: finite element discretization error and the truncation error of the nonlocal boundary operators. In particular, the truncation error caused by truncation operations is exponentially decayed when the parameter N is increased. Numerical experiment is included to illustrate the efficiency of the method. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 31: 1101–1118, 2015     

Accurate prediction of relative binding affinities of a series of HIV-1 protease inhibitors using semi-empirical quantum mechanical charge

A major challenge in computer-aided drug design is the accurate estimation of ligand binding affinity. Here, a new approach that combines the adaptive steered molecular dynamics (ASMD) and partial atomic charges calculated by semi-empirical quantum mechanics (SQMPC), namely ASMD-SQMPC, is suggested to predict the ligand binding affinities, with 24 HIV-1 protease inhibitors as testing examples. In the ASMD-SQMPC, the relative binding free energy (ΔG) is reflected by the average maximum potential of mean force (<PMF>_max) between bound and unbound states. The correlation coefficient (R²) between the <PMF>_max and experimentally determined ΔG is 0.86, showing a significant improvement compared with the conventional ASMD (R² = 0.52). Therefore, this study provides an efficient approach to predict the relative ΔG and reveals the significance of precise partial atomic charges in the theoretical simulations.     

Moving boundary truncated grid method: Multidimensional quantum dynamics

The moving boundary truncated grid (TG) method is used to study wave packet dynamics of multidimensional quantum systems. As time evolves, appropriate Eulerian grid points required for propagating a wave packet are activated and deactivated with no advance information about the dynamics. This method is applied to the Henon-Heiles potential and wave packet barrier scattering in two, three, and four dimensions. Computational results demonstrate that the TG method not only leads to a great reduction in the number of grid points needed to perform accurate calculations but also is computationally more efficient than the full grid calculations.