Conjugate gradient-based FLANN algorithms in nonlinear active noise control

The conjugate gradient (CG) method exhibits fast convergence speed than the steepest descent, which has received considerable attention. In this work, we propose two CG-based methods for nonlinear active noise control (NLANC). The proposed filtered-s Bessel CG (FsBCG)-I algorithm implements the functional link artificial neural network (FLANN) as a controller, and it is derived from the Matérn kernel to achieve enhanced performance in various environments. On the basis of the FsBCG-I algorithm, we further develop the FsBCG-II algorithm, which utilizes the Bessel function of the first kind to constrain outliers. As an alternative, the FsBCG-II algorithm has reduced computational complexity and similar performance as compared to the FsBCG-I algorithm. Moreover, the convergence property of the algorithms is analyzed. The proposed algorithms are compared with some highly cited previous works. Extensive simulation results demonstrate that the proposed algorithms can achieve robust performance when the noise source is impulsive, Gaussian, logistic, and time-varying.     

Adaptive finite-time fuzzy control for hybrid levitation system of maglev trains with active anti-lock constraints

The great risk of the suspension contact tremendously restricts the practical public service of hybrid maglev trains. If an operational train contacts to the guideway resulting in the “lock” state, it would cut down its lifetime or even endanger passenger safety. To address the deadlock problem of hybrid maglev trains, a novel adaptive finite-time fuzzy control with active anti-lock constraints is proposed in this paper. First, an efficient fuzzy-logic system is applied to approximate the hybrid levitation dynamics, not only precisely describing the system but also reducing computation burden. Moreover, by a novel nonlinear coordinate transformation, an anti-lock levitation controller is designed to prevent suspension contact between trains and guideways via the back-stepping technique. In the process, command filtering is utilized to circumvent the derivatives of virtual control variables and to address practical input constraints. Differing from the barrier Lyapunov function technique, the proposed nonlinear transformation helps to directly address both positive lower and upper boundaries. In addition, finite time convergence is achieved by the proposed scheme, which enjoys the characteristics of a fast and quantifiable response. Numerical simulations verify the theoretical results.     

Application of active disturbance rejection control in tank gun control system

The problem of position tracking for a tank gun control system with inertia uncertainty and external disturbance is investigated in this paper. The tank gun control system, demanding high tracking precision and stabilization precision, is a nonlinear system. Classical control methods are commonly used in the actual system, which is difficult to ensure high precision and high disturbance rejection capability. An active disturbance rejection control (ADRC) scheme is applied to guarantee the state variables of the closed loop system to converge to the reference state with the help of the extended state observer by estimating the inertia uncertainty and external disturbance. The basic theory of the ADRC is introduced here. According to the mathematical model, the parameters of ADRC are designed. Also, simulation results show that ADRC controller has advantages of high precision and high disturbance rejection ability. A comparison between ADRC and PID is also presented to show the effectiveness of the ADRC control strategy.     

基于压电陶瓷的车内噪声模糊控制技术研究

基于国内对汽车车内噪声控制标准的提升，运用目前国内外对噪声主动控制方面的研究成果，结合汽车自身特点，阐述了利用压电陶瓷对车内噪声进行主动控制的研究；并根据车内声学模态对压电陶瓷优化配置方法和基于智能模糊的控制策略进行探讨，最后通过对轿车车内噪声控制试验验证这种主动控制方法。     

Adaptive vibration control of a flexible structure based on hybrid learning controlled active mass damping

Natural disasters such as earthquakes and strong winds will lead to vibrations in ultra-high or high-rise buildings and even the damages of the structures. The traditional approaches resist the destructive effects of natural disasters through enhancing the performance of the structure itself. However, due to the unpredictability of the disaster strength, the traditional approaches are no longer appropriate for earthquake mitigation in building structures. Therefore, designing an effective intelligent control method for suppressing vibrations of the flexible buildings is significant in practice. This paper focuses on a single-floor building-like structure with an active mass damper (AMD) and proposes a hybrid learning control strategy to suppress vibrations caused by unknown time-varying disturbances (earthquake, strong wind, etc.). As the flexible building structure is a distributed parameter system, a novel finite dimension dynamic model is firstly constructed by assumed mode method (AMM) to effectively analyze the complex dynamics of the flexible building stucture. Secondly, an adaptive hybrid learning control based on full-order state observer is designed through back-stepping method for dealing with system uncertainties, unknown disturbances and immeasurable states. Thirdly, semi-globally uniformly ultimate boundedness (SGUUB) of the closed-loop system is guaranteed via Lyapunov’s stability theory. Finally, the experimental investigation on Quanser Active Mass Damper demonstrates the effectiveness of the presented control approach in the field of vibration suppression. The research results will bring new ideas and methods to the field of disaster reduction for the engineering development.     

Sliding mode control for active magnetic bearing system with flexible rotor

This paper presents the analysis and control of active magnetic bearing (AMB) systems with a flexible rotor. A sliding mode controller design scheme is proposed to compensate for the nonlinear effects of the AMB system. A nonlinear model of the AMB system with an electromagnetic actuator and a flexible rotor is proposed to facilitate the present system analysis and controller design. This nonlinear model takes into account the dynamics of the flexible rotor, the characteristics of the nonlinear electromagnetic suspended system, and the contact force between the auxiliary bearing and the shaft. This study also considers the auto-centering control of the AMB system when subjected to disturbances and variations in the system parameters. The numerical results show that the system exhibits a periodic motion and demonstrates high accuracy and robustness when operating under sliding mode control.     

进气系统噪声优化

随着汽车行业技术水平的不断进步,用户对汽车各项性能要求也越来越高,NVH性能是汽车重要性能指标之一,而进气系统的NVH性能是整车NVH性能重要的组成部分,加强对进气系统噪声控制是解决车辆噪声的一种有效途径。文章针对某款轿车在加速过程存在较大轰鸣声,并对车内噪声产生较大贡献问题,诊断出进气系统设计存在缺陷,通过合理设计消音元件对进气系统进行优化设计,并校验了增加消音元件之后的消声效果。结果表明,增加谐振腔和多孔管结构后,进气系统噪声水平改善明显,加速轰鸣声明显减弱,对整车内噪有着极大改观,提升了整车NVH品质。     

并联混合动力汽车能量控制策略的研究分析

蓄电池的问题一直是纯电动汽车发展的瓶颈,所以将混合动力汽车作为纯电动汽车发展的过渡期,来缓解日益严峻的环境和能源问题。而混合动力汽车研究的核心就是能量控制策略问题。文章首先对于并联混合动力汽车的驱动系统及不同工况下的驱动模式进行简要介绍,然后对并联混合动力汽车研究中常用的基于规则的控制策略和基于优化的控制策略进行分析研究,并指出了混合动力汽车控制策略的以后研究方向是基于优化算法的对控制策略的多目标进行研究。     

微电网混合储能系统设计

微电网中的光伏、风力及其他电源受外界条件影响不够稳定,将蓄电池和超级电容组成的混合系统应用于微电网能有效增强微电网的稳定性。DC/DC双向变换器,通过多滞环和PID控制可以将蓄电池和超级电容并联起来;将SVPWM技术和改进解耦应用于储能系统的并网系统中,SVPWM技术有效利用了直流电压,改进解耦控制方法减少了电网谐波含量和系统响应时间。将这些方法组合应用于储能系统的并网,提高微电网的稳定性。     

A novel hybrid filter-based fault diagnosis algorithm for switched systems with a dual noise term

This study considers state and fault estimation for a switched system with a dual noise term. A zonotopic and Gaussian Kalman filter for state estimation is designed to obtain state estimation interval in the presence of both stochastic and unknown but bounded (UBB) uncertainties. The switching state and fault state of the system are distinguished by detecting whether the system measurement date is within the bounds of its predicted output. Once the switched time is detected in the system, the filter zonotopic and Gaussian Kalman functions are initialized. Once the fault time is detected, a zonotopic and Gaussian Kalman filter-based fault estimator is constructed to estimate the corresponding faults. Finally, a numerical simulation is presented to demonstrate the accuracy and effectiveness of the proposed algorithm.     

A hybrid approximation scheme for discretizing constrained quadratic optimal control problems

In this paper, a composite Chebyshev finite difference method for solving linear quadratic optimal control problems with inequality constraints on state and control variables is introduced. This method is an extension of Chebyshev finite difference scheme and is based on a hybrid of block-pulse functions and Chebyshev polynomials using the well known Chebyshev–Gauss–Lobatto nodes. The excellent properties of hybrid functions are used to convert optimal control problem into a mathematical programming problem whose solution is much more easier than the original one. Various types of optimal control problems are investigated to demonstrate the effectiveness of the proposed approximation scheme. The method is simple, easy to implement and provides very accurate results.     

Hierarchical control of hybrid direct current microgrid with variable structure based sliding mode control and fuzzy energy management system

The recent transition in power generation and consumption is based on the integration of renewable energy sources using DC microgrids. To facilitate this integration, a multi-source DC microgrid structure with wind, photovoltaics, fuel cell and hybrid energy storage system including battery and supercapacitor is presented in this paper. These sources are linked to a DC-bus via DC-DC converters. A hierarchical control strategy with a device and a system-level control for coordinated control between energy sources and their storage devices is proposed. In the device-level control, a variable structure based sliding mode control is applied to regulate the DC bus voltage and to ensure global asymptotic stability. Whereas, the system-level control compensates for the supply and demand mismatches by using a rule-based fuzzy system. To verify the effectiveness of the proposed scheme and the superiority of one controller over another, the proposed controllers are simulated and compared in the MATLAB/Simulink environment under varying load and weather data conditions. Results show that super twisting sliding mode control had negligible chattering as well as better convergence as compared to controllers. Furthermore, the efficiency of the developed scheme is validated by controller hardware in loop experiments.     

A hybrid dielectrophoretic system for trapping of microorganisms from water

Assessment of the microbial safety of water resources is among the most critical issues in global water safety. As the current detection methods have limitations such as high cost and long process time, new detection techniques have transpired among which microfluidics is the most attractive alternative. Here, we show a novel hybrid dielectrophoretic (DEP) system to separate and detect two common waterborne pathogens, Escherichia coli (E. coli), a bacterium, and Cryptosporidium parvum (C. parvum), a protozoan parasite, from water. The hybrid DEP system integrates a chemical surface coating with a microfluidic device containing inter-digitated microelectrodes to impart positive dielectrophoresis for enhanced trapping of the cells. Trimethoxy(3,3,3-trifluoropropyl) silane, (3-aminopropyl)triethoxysilane, and polydiallyl dimethyl ammonium chloride (p-DADMAC) were used as surface coatings. Static cell adhesion tests showed that among these coatings, the p-DADMAC-coated glass surface provided the most effective cell adhesion for both the pathogens. This was attributed to the positively charged p-DADMAC-coated surface interacting electrostatically with the negatively charged cells suspended in water leading to increased cell trapping efficiency. The trapping efficiency of E. coli and C. parvum increased from 29.0% and 61.3% in an uncoated DEP system to 51.9% and 82.2% in the hybrid DEP system, respectively. The hybrid system improved the cell trapping by encouraging the formation of cell pearl-chaining. The increment in trapping efficiency in the hybrid DEP system was achieved at an optimal frequency of 1 MHz and voltage of 2.5 V_pp for C. parvum and 2 V_pp for E. coli, the latter is lower than 2.5 V_pp and 7 V_pp, respectively, utilized for obtaining similar efficiency in an uncoated DEP system.     

内燃机噪声测试系统设计

内燃机的开发利用给我们带来巨大便利的同时,也给我们带来烦躁的噪音,文章通过分析内燃机噪声产生原因,提出降噪措施,并通过采用朗德DATaRec 4 DIC24模块采集系统,开发出一套先进的多通道内燃机噪声测试系统,为内燃机降噪提供准确数据。     

Optimal control of a flywheel energy storage system with a radial flux hybrid magnetic bearing

This paper describes the design and implementation of digital controllers for a flywheel energy storage device that incorporates a radial flux hybrid permanent magnetic bearing. Although the uncontrolled device is asymptotically stable, active control is required to: (i) ensure that a finite radial air gap is maintained at all times, and (ii) attenuate the oscillations of the flywheel which reduce the efficiency of the motor generator. The paper presents the design of gain scheduled discrete time linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controllers for this rotordynamic system. Real time experiments are conducted to investigate the performance of the controllers. The result indicates that the LQR controller with approximate system velocities is easier to implement than the LQG controller, and also provides superior performance.     

舰艇舱室噪声控制技术研究

舰艇噪声是舰艇舱室环境主要有害因素之一。文章对目前舰艇舱室噪声现状进行了介绍,对主要噪声控制技术进行了研究,并对舰艇舱室噪声控制给出建议。     

Robust state-feedback control design for active suspension system with time-varying input delay and wheelbase preview information

This paper develops a robust state-feedback controller for active suspension system with time-varying input delay and wheelbase preview information in the presence of the parameter uncertainties. By employing system augmentation technique, a multi-objective control optimization model is first established and then this controller design is converted to a static full-state feedback controller design with robust H_∞ and generalized H₂ performance, wherein the model-dependent control gain is evaluated by transforming the related nonlinear matrix inequalities into their corresponding linear matrix inequality forms based on Lyapunov theory, and then LMI (Linear-Matrix-Inequality) technique is applied to solve and obtain the desired controller. A numerical simulation case is finally provided to reveal the effectiveness and advantages of the proposed controller.