Dynamic Pricing Research for Container Terminal Handling Charges based on Demand Forecast

A dynamic pricing model was established based on forecasting the demand for container handling of a specific shipping company to maximize terminal profits to solve terminal handling charges under the changing market environment.It assumes that container handling demand depends on the price and the unknown parameters in the demand model.The maximum quasi-likelihood estimation(MQLE)method is used to estimate the unknown parameters.Then an adaptive dynamic pricing policy algorithm is proposed.At the beginning of each period,through dynamic pricing,determining the optimal price relative to the estimation value of the current parameter and attach a constraint of differential price decision.Meanwhile,the accuracy of demand estimation and the optimality of price decisions are balanced.Finally,a case study is given based on the real data of Shanghai port.The results show that this pricing policy can make the handling price converge to the stable price and significantly increase this shipping company’s handling profit compared with the original“contractual pricing”mechanism.

Adaptive Predefined-Time Attitude Tracking Control for Quadrotor Using a Novel Terminal Sliding Mode Approach

This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a terminal sliding mode is constructed.The upper bound of convergence time in the proposed scheme can be adjusted by the explicit parameters during the design process of the controller.In addition,it is proved that the attitude tracking error will converge within two periods of the preset time.These two periods are set between two ranges:From the initial values to the sliding mode surface and from the sliding mode surface to the region near the origin.Furthermore,an adaptive law is adopted to eliminate unknown external disturbances and the effects of the uncertainties in the quadrotor model,so it is unnecessary to require the prior knowledge of the upper bound of the perturbations.Simulation results are produced and comparative case studies are carried out to demonstrate that the proposed scheme has faster convergence speed and smaller tracking errors.

基于自适应Terminal滑模的混沌振荡控制

针对电力系统负荷扰动满足一定条件时就会产生混沌振荡现象,提出了一种自适应Terminal滑模混沌控制方法。利用Lyapunov指数证明了系统存在混沌振荡,应用简单电力系统分析了周期性负荷扰动下的动力学行为,设计了Terminal滑模动态使得系统能够快速收敛,给出了扰动的自适应律。应用Matlab/Simulink仿真平台对含噪声和不含噪声的电力系统进行仿真验证。仿真结果表明,该控制方法能够有效地镇定电力系统混沌振荡。

Terminal滑模自适应控制实现一类不确定混沌系统的同步

应用T erm ina l滑模控制技术和选择指数趋近律来综合滑模控制器,实现一类混沌系统的状态同步.在控制器中引入一类简单的自适应律,用以在线估计界参数.该设计方案消除了滑模控制的到达阶段,状态始终保持在滑模面上,并能在有限时间内趋近于原点.与一般滑模控制同步实现相比,具有更小的同步时间和鲁棒性.通过对Du ff-ing-Ho lm es系统的同步仿真,验证了该方法的可行性.

Simulation and optimization for airdrop adaptability of overweight equipment

Airbag buffer process was analyzed with the aid of aerodynamic and thermodynamic methods.Based on the current structure of the airbag,the terminal velocity was too high.Therefore,the research on the diameter and height of the airbag was done and the feasible design area was found.With the optimized structure parameters,the airbag buffer experiment under normal conditions was conducted.Furthermore,the residual height and internal pressure of the airbag as well as the terminal velocity and acceleration of the airdrop were obtained.The experiment results show that the optimized airbag is feasible for 20 t cargo airdrop.

不确定性空间机器人自适应Terminal滑模控制方法

分析了空间机器人本体质量变化和负载情况变化对系统动力学不确定性的影响,并针对空间机器人操作负载变化显著的特点,设计了一种自适应Terminal滑模控制方法。利用RBF神经网络在线学习系统的不确定性上界,系统状态始终保持在滑模面上,并能保证系统控制误差在有限时间内收敛。以两自由度空间机器人为对象,对不同负载情况的运动进行了仿真,结果表明这种滑模控制方法对系统负载变化不敏感,并能保证期望控制精度。

高超声速飞行器的干扰补偿Terminal滑模控制

研究了一种基于干扰补偿Terminal滑模的高超声速飞行器姿态控制方法.针对传统Terminal滑模控制存在的奇异问题,提出了一种简单的改进型Terminal滑模面,通过在平衡点附近从非线性滑模面切换至高增益线性滑模面,避免了控制奇异问题,同时保持了较高的收敛速度,并对改进Terminal滑模控制在干扰作用下的误差收敛特性进行了理论分析.为进一步提高控制的鲁棒性和控制精度,设计了扩张状态观测器对干扰进行估计和补偿.进行了六自由度数学仿真验证,仿真结果表明:该方法可有效提高控制系统的控制性能和鲁棒性.

多机电力系统自适应鲁棒Terminal滑模励磁控制

设计了多机电力系统发电机励磁的自适应鲁棒Terminal滑模控制器,将L2增益干扰抑制、自适应逆推法、Terminal滑模控制相结合,可以自适应估计发电机的不确定阻尼系数,对扰动具有鲁棒性。给出了控制器的设计过程。针对2区域4机系统的仿真结果表明,所设计的自适应鲁棒Terminal滑模励磁控制器能够快速抑制功率振荡,有效提高电力系统的暂态稳定性,并保持机端电压的恒定。

统一混沌系统的指数型超曲面terminal滑模同步控制

讨论了一类统一混沌系统的指数型超曲面terminal滑模控制同步问题,并且针对初始状态离原点的不同,设计了3种超曲面,使得在系统初始状态远离平衡点和接近平衡点的情况下,均能较快地实现同步,从而弥补了接近平衡点收敛速度慢的不足.而且由于指数自适应环节的引入,使得滑模面的形式得到统一与简化,收敛性能得到进一步优化.最后仿真结果表明了该方案的有效性.

汽轮发电机自适应Terminal滑模综合控制

提出了汽轮发电机励磁与汽门协调Terminal滑模控制。针对发电机综合控制存在的两个输入变量,通过构造两个非奇异的Terminal滑模面,实现解耦控制。Terminal滑模面中含有非线性函数,使得误差能够快速收敛,从而取得良好的控制效果。利用自适应律实时估计扰动上界,从而使控制器具有很强的鲁棒性。通过李亚普洛夫理论证明了控制系统的稳定性。仿真结果表明,所设计的汽轮发电机自适应Terminal滑模综合控制器能够快速阻尼功率振荡,提高电力系统的稳定性,维持机端电压。

配变监控终端中TA二次侧短路的在线检测方法

提出了一种利用零序、正序和负序电流综合判断TA二次短路的测量方法。该方法利用了TA在不同接法中二次侧出现短路时各序电流值的不同组合的特性,对TA二次侧短路进行判断。该判据能够同时适用于三相三线制中的V型接线和三相四线制中Y型接线的TA二次侧电流短路的检测。现场运行实践证实了该判据的可靠性和实用性。

自适应模糊全局快速Terminal滑模控制方法

提出了一种自适应模糊全局快速Terminal滑模控制方法,在参数不确定性和外干扰情况下,为解决系统的非线性不确定性提供了一种新途径。与传统模糊Terminal滑模控制相比,通过采用模糊逻辑系统来逼近未知系统函数和开关项;鲁棒自适应律用来减小逼近误差,从而有效降低抖振;证明了该控制方案的稳定性,并将该方案应用在倒立摆系统中。仿真结果验证了该方案的有效性。

发电机自适应Terminal滑模励磁控制

建立了单机无穷大系统的励磁控制数学模型,设计了一种自适应Terminal滑模励磁控制器。通过在滑模面加入非线性函数,使得误差能够快速收敛,从而取得良好的控制效果。同时考虑了系统中存在未知上界的不确定扰动,在设计中加入了自适应环节,实时估计扰动上界,从而使控制器具有较强的鲁棒性。根据李亚普洛夫理论证明了所设计控制系统的稳定性。仿真结果表明,无论是小扰动还是大扰动下均能有效提高系统稳定性,维持机端电压,效果优于自适应逆推滑模励磁控制。

基于干扰观测器的一类不确定非线性系统自适应二阶动态terminal滑模控制

针对一类不确定非线性系统的跟踪控制问题,在考虑建模误差、参数不确定和外部干扰情况下,以其拥有良好的跟踪性能以及强鲁棒性为目标,提出基于回归扰动模糊神经网络干扰观测器(recurrent perturbation fuzzy neural networks disturbance observer,RPFNNDO)的鲁棒自适应二阶动态terminal滑模控制策略.将回归网络、模糊神经网络和sine-cosine扰动函数各自优势相结合,给出一种回归扰动模糊神经网络结构,提出RPFNNDO设计方法,保证干扰估计准确性;构造基于带有指数函数滑模面的二阶快速terminal滑模面,给出其控制器设计过程,避免了滑模到达阶段、传统滑模的抖振问题,采用具有指数收敛的鲁棒项抑制干扰估计误差对系统跟踪性能的影响,利用Lyapunov理论证明闭环系统的稳定性;将该方法应用于混沌陀螺系统同步控制仿真实验,结果表明所提方法的有效性.

基于复杂干扰估计的高速NSV鲁棒自适应模糊Terminal滑模控制

针对近空间飞行器大包络高动态飞行运动特性,建立了包含复杂干扰的有效动力学系统用以描述运动过程,对系统中由于飞行物理环境产生的复杂干扰,设计了有效估计的非线性干扰观测器,有效保证了观测误差的收敛性能,采用模糊系统逼近由气动、结构变化产生的系统与增益函数不确定项,基于此设计了飞行控制系统的鲁棒自适应模糊Terminal滑模控制方案,利用Lyapunov稳定性原理证明了闭环系统的鲁棒稳定性,控制器有效抑制了不确定项与复杂干扰对系统的影响,实现了NSV复杂环境下高速运动的鲁棒自适应自主控制,仿真研究证明了控制方法的正确性与有效性。

一类不确定系统的自适应非奇异Terminal滑模控制

提出针对一类不确定系统的自适应非奇异Terminal滑模控制。确定含非线性项的滑模面,通过构造李亚普洛夫函数的方式确定控制器结构,设计自适应增益控制律实时估计不确定参数,并考虑外扰动的影响,证明控制系统的稳定性和鲁棒性。仿真结果验证自适应非奇异Terminal滑模控制器能够使不确定系统状态变量快速收敛。

FTASMC在光电跟踪系统中的应用

针对存在多种扰动源的光电跟踪系统,提出有限时间自适应滑模复合控制(finite time adaptive sliding mode compound control,FTASMC)策略。首先,将各类扰动看做等效干扰,设计基于super-twisting的高阶滑模干扰补偿器对其进行快速的估计补偿;其次,为提高控制精度,提出一种新的双幂次自适应滑模控制(double power adaptive sliding mode controller,DASMC)策略,在控制器设计过程中,采用双幂次理论结合终端滑模控制理论设计一种新型滑模面,并通过设计一种新型自适应快速滑模趋近律,得到能够保证系统在有限时间内全局快速收敛的控制率。最后,使用Lyapunov理论及实验仿真证明所提出的控制策略有效。

不确定扰动分数阶混沌系统自适应Terminal滑模同步

针对带扰动不确定分数阶混沌系统的同步问题,基于自适应Terminal滑模控制,设计了一种分数阶非奇异Terminal滑模面,保证误差系统沿着滑模面在有限时间内稳定至平衡点,在系统外部扰动和不确定性的边界事先未知的情况,设计了自适应控制率,在线估计未知边界,使得同步误差轨迹能到达滑模面。最后,以三维分数阶Chen系统和四维分数阶Lorenz超混沌系统为例,利用所设计的自适应Terminal滑模控制器进行同步仿真,验证了所给方法是有效性和可行性。

Adaptive Terminal Sliding Mode Control for Rigid Robotic Manipulators

In order to apply the terminal sliding mode control to robot manipulators,prior knowledge of the exact upper bound of parameter uncertainties,and external disturbances is necessary.However,this bound will not be easily determined because of the complexity and unpredictability of the structure of uncertainties in the dynamics of the robot.To resolve this problem in robot control,we propose a new robust adaptive terminal sliding mode control for tracking problems in robotic manipulators.By applying this adaptive controller,prior knowledge is not required because the controller is able to estimate the upper bound of uncertainties and disturbances.Also,the proposed controller can eliminate the chattering effect without losing the robustness property.The stability of the control algorithm can be easily verified by using Lyapunov theory.The proposed controller is tested in simulation on a two-degree-of-freedom robot to prove its effectiveness.

Adaptive Backstepping Terminal Sliding Mode Control Method Based on Recurrent Neural Networks for Autonomous Underwater Vehicle

The trajectory tracking control problem is addressed for autonomous underwater vehicle(AUV) in marine environ?ment, with presence of the influence of the uncertain factors including ocean current disturbance, dynamic modeling uncertainty, and thrust model errors. To improve the trajectory tracking accuracy of AUV, an adaptive backstepping terminal sliding mode control based on recurrent neural networks(RNN) is proposed. Firstly, considering the inaccu?rate of thrust model of thruster, a Taylor’s polynomial is used to obtain the thrust model errors. And then, the dynamic modeling uncertainty and thrust model errors are combined into the system model uncertainty(SMU) of AUV; through the RNN, the SMU and ocean current disturbance are classified, approximated online. Finally, the weights of RNN and other control parameters are adjusted online based on the backstepping terminal sliding mode controller. In addition, a chattering?reduction method is proposed based on sigmoid function. In chattering?reduction method, the sigmoid function is used to realize the continuity of the sliding mode switching function, and the sliding mode switching gain is adjusted online based on the exponential form of the sliding mode function. Based on the Lyapu?nov theory and Barbalat’s lemma, it is theoretically proved that the AUV trajectory tracking error can quickly converge to zero in the finite time. This research proposes a trajectory tracking control method of AUV, which can e ectively achieve high?precision trajectory tracking control of AUV under the influence of the uncertain factors. The feasibility and e ectiveness of the proposed method is demonstrated with trajectory tracking simulations and pool?experi?ments of AUV.