Optimization approaches of aircraft flight path reducing noise: Comparison of modeling methods

An optimization model of flight paths is designed for minimizing aircraft noise at reception points around airports. It is stated as a nonconvex and nonlinear control problem governed by ordinary differential equations using a jet noise model. The vertical plan and the space cases have been solved using two approaches, one direct and one indirect. The objective was initially to apply these two methods, then to carry out comparisons, and finally to retain the method which would be applied for the general case including engine and airframe sources. Results showed that the direct method is adapted for solving the problem and can be implemented with moderate computing times. It is sufficient to analyze the constrained flight path optimization of commercial aircraft reducing noise levels. The three-segment approach procedure has been obtained as an optimized flight path which can substantially reduce noise levels. This modified approach procedure has been examined and could benefit both airlines and communities.     

Switching Adaptive Control with Applications on Robot Manipulators

This paper concentrates on the study of logic-based switching adaptive control. Two different cases will be considered. In the first case, the finite time stabilization problem for a class of nonlinear system is studied. Based on the recently developed adding a barrier power integrator technique, a new logic-based switching adaptive control method is proposed. In contrast with the existing results, finite time stability can be achieved when the considered systems contain both fully unknown nonlinearties and unknown control direction. Moreover, the proposed controller has a very simple structure and no approximation methods, e.g., neural networks/fuzzy logic, are needed. In the second case, the sampled-data control for a class of nonlinear system is investigated. New sampled-data logic-based switching mechanism is proposed. Compared with previous works, the considered nonlinear system has an uncertain linear growth rate. The control parameters and the sampling time can be adjusted adaptively to render the exponential stability of the closed loop system. Applications in robot manipulators are conducted to verify the proposed results.     

基于感知模糊自适应蚁群算法的非线性PID控制

随着系统复杂度的提高和对象不确定性因素的增加,为克服线性PID动态性能和稳态性能差的缺陷,分析了非线性PID控制器各控制参数对误差的理想变化过程,构造非线性PID控制器。由于增益参数大量增加,传统参数优化方法不再适用,在分析蚁群算法的基础上,提出了基于感知自适应蚁群算法,并加入模糊自适应信息素更新机制,用于优化非线性PID控制器的设计方法。通过仿真实验将该控制器与基于蚁群算法的非线性PID控制器和基于蚁群算法、Z-N法的PID控制器进行对比,并对控制性能和收敛性能进行了分析,结果表明该算法有效克服了传统蚁群算法收敛速度较慢、容易陷入局部最优而停滞的缺陷,该控制器具有更好的动态性能和稳态性能。     

迟滞混沌神经元/网络的控制策略及应用研究

为了保持神经网络在优化计算求解过程中结构不被改变, 以迟滞混沌神经元和迟滞混沌神经网络为研究对象, 提出了一种基于滤波跟踪误差的控制策略来实现神经元/网络的稳定控制. 采用该控制策略, 在不改变非线性特性发生机理的情况下, 神经元/网络可实现函数优化计算问题的求解. 所设计的控制律包含两部分: 一部分是系统进入滤波跟踪误差面时的等效控制部分, 另一部分为确保系统快速进入滤波跟踪误差面的控制部分. 采用Lyapunov方法对神经元/网络的控制进行了稳定性证明. 根据待寻优函数直接求得神经元的控制律, 在该控制律的作用下, 神经元/网络可逐渐稳定到优化函数的极值点, 从而实现优化问题的求解, 仿真实验结果验证了该控制方法在优化计算中的可行性和有效性.     

Tracking Consensus for Second-Order Multi-Agent Systems with Nonlinear Dynamics in Noisy Environments

This paper investigates the leader-following tracking consensus problem for second-order multi-agent systems with time delays and nonlinear dynamics in noisy environments on the conditions of fixed and switching directed topologies. Based on a novel velocity decomposition technique and stochastic analysis, a measurement-based distributed tracking control protocol is proposed, under which all agents can track the leader in mean square. Simulation results are also given to illustrate the effectiveness of the proposed protocol.     

一种热集成系统的动态多智能体微分进化算法

针对热集成系统换热网络存在的严重非凸非线性与多维多极值问题,提出动态多智能体微分进化算法.结合动态更新策略,并引入多智能体算法的环境感知能力,改进微分进化算法的种群生成方式与变异机制,并增强在大规模复杂非线性系统中的全局搜索能力.通过10SP2与9SP1换热网络经典算例优化,得到最佳年综合费用,体现出了改进算法更优的全局搜索能力.     

离散混沌系统的最小能量控制

对于离散混沌系统的最小能量控制问题，提出了一种框架性方法，该方法具有通用性.首先，设计一个二次目标函数，同时把混沌系统分解为线性部分和非线性部分两项和.然后，提出了求解非线性最优控制问题的两级算法：第一级对混沌系统中的非线性部分进行预估，以使原系统变为带有常数项的线性系统；第二级用动态规划求解一个非典型线性二次最优控制问题，并把解返回第一级，第一级根据第二级的解对非线性部分重新预估.这样通过两级间不断的信息交换，最终得到混沌系统的最优控制律.该方法不仅实现了对混沌系统的控制，而且在整个控制过程中消耗的控制能量最小. 关键词： 混沌系统 两级优化 最优控制     

Consensus of multiple autonomous underwater vehicles with double independent Markovian switching topologies and timevarying delays

A new method in which the consensus algorithm is used to solve the coordinate control problems of leaderless multiple autonomous underwater vehicles(multi-AUVs) with double independent Markovian switching communication topologies and time-varying delays among the underwater sensors is investigated.This is accomplished by first dividing the communication topology into two different switching parts,i.e.,velocity and position,to reduce the data capacity per data package sent between the multi-AUVs in the ocean.Then,the state feedback linearization is used to simplify and rewrite the complex nonlinear and coupled mathematical model of the AUVs into a double-integrator dynamic model.Consequently,coordinate control of the multi-AUVs is regarded as an approximating consensus problem with various time-varying delays and velocity and position topologies.Considering these factors,sufficient conditions of consensus control are proposed and analyzed and the stability of the multi-AUVs is proven by Lyapunov-Krasovskii theorem.Finally,simulation results that validate the theoretical results are presented.     

Dynamics of Transiently Chaotic Neural Network and Its Application to Optimization

Through adding a nonlinear self-feedback term in the evolution equations of nerual network,we introduced a transiently chaotic neural network model.In order to utilize the transiently chaotic dynamics mechanism in optimization problem efficiently,we have analyzed the dynamical pocedure of the transiently chaotic neural network model and studied the function of the crucial bifurcation parameter which governs the chaotic behavior of the system.Based on the dynamical analysis of the transiently chaotic neural network model,Chaotic annealing algorithm is also examined and improved.As an example,we applied chaotic annealing method to the traveling salesman problem and obtained good results.     

Optimizing linear optics quantum gates

In this Letter, the problem of finding optimal success probabilities of linear optics quantum gates is linked to the theory of convex optimization. It is shown that by exploiting this link, upper bounds for the success probability of networks realizing single-mode gates can be derived, which hold in generality for postselected networks of arbitrary size, any number of auxiliary modes, and arbitrary photon numbers. As a corollary, the previously formulated conjecture is proven that the optimal success probability of a nonlinear sign shift without feedforward is 1/4, a gate playing the central role in the scheme of Knill-Laflamme-Milburn for quantum computation. The concept of Lagrange duality is shown to be applicable to provide rigorous proofs for such bounds, although the original problem is a difficult nonconvex problem in infinitely many objective variables. The versatility of this approach is demonstrated.     

Birkhoff系统的离散最优控制及其在航天器交会对接中的应用

由于非线性,最优控制问题通常依赖于数值求解,即通过离散目标泛函和受控运动方程转化为一有限维的非线性最优化问题.最优控制问题中的受控运动方程在表示为受控Birkhoff方程的形式之后,可以利用受控Birkhoff方程的离散变分差分格式进行离散.与按照传统差分格式近似受控运动方程相比,此途径可以诱导更加真实可靠的非线性最优化问题,进而也会诱导更加精确有效的离散最优控制.应用于航天器交会对接问题,该种数值求解最优控制问题的方法在较大时间步长的情况下仍然求得了一个有效实现交会对接的离散最优控制.模拟结果验证了该方法的有效性.     

Energy-Efficient Trajectory Optimization for UAV-Based Hybrid FSO/RF Communications with Buffer Constraints

This paper focuses on an unmanned aerial vehicle (UAV) assisted hybrid free-space optical (FSO)/radio frequency (RF) communication system. Considering the rate imbalance between the FSO and RF links, a buffer is employed at the UAV. Initially, theoretical models of energy consumption and throughput are obtained for the hybrid system. Based on these models, the theoretical expression of the energy efficiency is derived. Then, a nonconvex trajectory optimization problem is formulated by maximizing the energy efficiency of the hybrid system under the buffer constraint, velocity constraint, acceleration constraint, start–end position constraint, and start–end velocity constraint. By using the sequential convex optimization and first-order Taylor approximation, the nonconvex problem is transformed into a convex one. An iterative algorithm is proposed to solve the problem. Numerical results verify the efficiency of the proposed algorithm and also show the effects of buffer size on a UAV’s trajectory.     

SISO仿射非线性系统自适应变结构BPNN控制

为了更好地消除抖振,提高复杂非线性系统的控制效果,针对一类典型SISO仿射非线性系统,提出了一种新的变结构神经网络自适应控制策略(VSYNC)。其中,对于系统未知非线性函数,将神经网络用作估计器。对控制输入加入连续函数项,其可以根据状态点和滑动切换面之间的距离自适应地调节不连续的控制变量,从而使变结构控制策略得到了显著提高。所提出的控制方法能够有效地抑制周围切换面的抖振,保证了系统地动态性能,同时还能够消除系统的稳态误差。仿真结果表明,该方法具有较高的控制精度和鲁棒性。     

Numerical study on a compact all-semiconductor-optical-amplifier Sagnac interferometer device

The nonlinear switching effect of an all-semiconductor-optical-amplifier Sagnac interferometer is numerically investigated. The device, stemming from the conventional nonlinear optical loop mirror made of fiber, has a much more compact size and a latency several hundred times smaller than the conventional ones. Numerical simulations are conducted for the case of cw signal operation. It is found that the nonlinear coupling in the MMIWA and the lateral field redistribution as well as the amplification of the signal through the loop structure contribute together to the nonlinear switching. Besides investigating the physical mechanism of the device, we vary relevant parameters to evaluate their influences on device performance. The numerical simulations show good agreement in trend with the experimental results.     

Using modified Mach-Zehnder interferometer to get better nonlinear correction term of an isotropic nonlinear material

Nonlinear materials have been well established as photo refractive switching material. Important applica- tions of isotropic nonlinear materials are seen in self-focusing, defocusing phenomena, switching systems, etc. The nonlinear correction term is basically responsible for the optical switches. Mach-Zehnder inter- ferometer （MZI） is a well-known arrangement for determining the above correction term, but there are some major problems for finding out the term by MZI. We propose a new method of finding the nonlinear correction term as well as the second order nonlinear susceptibility of the materials by using a modified MZI system. This method may be used to find out the above parameters for any unknown nonlinear material.     

电流型脉冲序列控制Buck变换器工作在电感电流连续导电模式时的多周期行为

脉冲序列控制(PT)是一种离散的非线性开关变换器控制方法,具有瞬态响应快、无需补偿网络、控制电路实现简单等优点.根据控制脉冲的产生方式不同,脉冲序列控制可分为电压型脉冲序列控制(voltage-mode PT,VM-PT)和电流型脉冲序列控制(current-mode PT,CM-PT).研究表明,工作于电感电流连续导电模式(continuous conduction mode,CCM)与工作于电感电流断续导电模式(discontinuous conduction mode)的VM-PT控制开关变换器的工作特性存在明显差别,VM-PT控制CCM开关变换器存在的低频振荡现象严重影响了其稳态及瞬态性能.目前,对CM-PT控制CCM开关变换器的工作特性还未见相关报道.研究了CM-PT控制CCM开关变换器的工作特性,对其控制参数以及稳定工作域进行了分析.分析结果表明,通过参数的合理设计,虽然可以避免低频振荡现象的发生以及开关管不能正常关断的问题,但存在变换器功率范围窄的缺点.最后针对这一缺点提出了一种改进的控制方法.     

Control of a unique active vibration isolator with a phase compensation technique and automatic on/off switching

This work examines the characteristics of a unique active vibration isolator and develops a control strategy for it. The proposed active vibration isolator is introduced and its dynamic model is presented. A characterization study is conducted to identify system parameters. It is shown that with a simple proportional feedback the closed-loop system has a very narrow stability margin due to the inherent dynamics of the actuator. To improve the stability of the closed-loop system and enhance the performance of vibration isolation, a phase compensator is incorporated in the control scheme. An optimization problem is formulated to determine the optimum controller parameters by minimizing the 2nd norm of the displacement transmissibility. Both absolute position feedback and relative position feedback are considered. In real time implementation, an automatic on/off switching strategy is devised to take full advantage of both the active isolator and passive isolator. The experimental results show that with the proposed control scheme, the isolator is capable of suppressing base excitations effectively.     

Truss optimization on shape and sizing with frequency constraints based on orthogonal multi-gravitational search algorithm

Structural optimization on shape and sizing with frequency constraints is well-known as a highly nonlinear dynamic optimization problem with several local optimum solutions. Hence, efficient optimization algorithms should be utilized to solve this problem. In this study, orthogonal multi-gravitational search algorithm (OMGSA) as a meta-heuristic algorithm is introduced to solve truss optimization on shape and sizing with frequency constraints. The OMGSA is a hybrid approach based on a combination of multi-gravitational search algorithm (multi-GSA) and an orthogonal crossover (OC). In multi-GSA, the population is split into several sub-populations. Then, each sub-population is independently evaluated by an improved gravitational search algorithm (IGSA). Furthermore, the OC is used in the proposed OMGSA in order to find and exploit the global solution in the search space. The capability of OMGSA is demonstrated through six benchmark examples. Numerical results show that the proposed OMGSA outperform the other optimization techniques.     

不同时变延迟下的多AUV编队协调控制

针对无领航者AUV编队协调控制问题,提出了一种不同时变通信延迟下的一致性协调控制方法。首先考虑到AUV之间水下通信存在时间延迟和数据丢失的问题,利用状态反馈线性化理论处理AUV数学模型中的非线性耦合项,从而将复杂的AUV模型转换为双积分器动态模型。其次,针对不同延迟通信情况,设计了位置和速度双独立的拓扑结构以减少编队成员之间发送每个数据包中的数据量。最后,提出了无领航者的多AUV稳定条件,进而将多AUV编队控制问题看作是一致性问题,基于Laypunov-Razumikhin定理证明时延多AUV编队系统的稳定性。该控制方法不仅能够克服不同时变延迟和数据丢失对编队的影响,使所有以随机位置和速度出发的AUV的三维轨迹均能达到一致状态,同时能抑制外界干扰。仿真结果与所提控制方法理论结果一致。     

Secrecy energy efficiency optimization for multiuser massive MIMO wiretap systems with transmit antenna selection

Massive multiple-input-multiple-output (Massive MIMO) significantly improves the capacity of wireless communication systems. However, large-scale antennas bring high hardware costs, and security is a vital issue in Massive MIMO networks. To deal with the above problems, antenna selection (AS) and artificial noise (AN) are introduced to reduce energy consumption and improve system security performance, respectively. In this paper, we optimize secrecy energy efficiency (SEE) in a downlink multi-user multi-antenna scenario, where a multi-antenna eavesdropper attempts to eavesdrop the information from the base station (BS) to the multi-antenna legitimate receivers. An optimization problem is formulated to maximize the SEE by jointly optimizing the transmit beamforming vectors, the artificial noise vector and the antenna selection matrix at the BS. The formulated problem is a nonconvex mixed integer fractional programming problem. To solve the problem, a successive convex approximation (SCA)-based joint antenna selection and artificial noise (JASAN) algorithm is proposed. After a series of relaxation and equivalent transformations, the nonconvex problem is approximated to a convex problem, and the solution is obtained after several iterations. Simulation results show that the proposed algorithm has good convergence behavior, and the joint optimization of antenna selection and artificial noise can effectively improve the SEE while ensuring the achievable secrecy rate.