带有迭代学习外环的快速路入口匝道无模型自适应预测控制

针对快速路交通系统复杂时变以及难以建模的特点,首先,本文设计了基于无模型自适应预测控制的快速路入口匝道控制方案.其次,根据快速路交通系统具有重复性特点,本文在无模型自适应预测控制方法的基础上引入开环迭代学习控制,提出一种带有迭代学习前馈外环的无模型自适应入口匝道预测控制方案.相比无模型自适应预测控制方案,该方案可以利用迭代学习前馈控制器补偿系统可重复扰动,实现系统的完全跟踪.值得说明的是,预测控制器和学习控制器可以独立工作也可以联合工作.最后,文章给出了控制方案的收敛性分析,并通过交通流仿真验证了所提控制方案的有效性.     

基于移动通信网的物联网拥塞控制方案研究

介绍了物联网的基本概念、业务特征,并对物联网的拥塞控制需求、核心网侧和无线侧拥塞控制方案进行了详细的研究,对不同方案进行分析比较,提出了基于移动通信网的物联网拥塞控制方案建议。     

飞机纵向运动模型参考反推自适应PID控制

为克服飞行控制系统设计中传统增益规划方案的缺点,提出一类飞机纵向运动模型参考反推自适应PID控制方案,并给出了该方案的具体设计过程和跟踪性能改善方法．理论分析和数值仿真结果表明．该方案兼具反推自适应控制和PID控制的优点．即：无需知道被控对象的精确数学模型,控制器结构简单,鲁棒性强,在不增大控制增益的前提下具有良好的跟踪性能．     

用于入侵容忍数据库系统的多阶段控制技术

传统入侵容忍数据库系统的破坏控制是一阶的,对象直到破坏评估器确认其受到破坏才被控制,时间延迟导致破坏的扩散而影响数据库系统的可用性,针对这个问题提出了多阶段破坏控制方案。给出了多阶段破坏控制技术模型,及多阶段破坏控制方案中各阶段的任务。最后,给出了多阶段破坏控制各阶段的效率分析。多阶段破坏控制方案有效地拒绝了破坏扩散,保证了数据库系统的可用性。     

操作器的PID自适应控制

利用操作器动力学模型的性质,提出了一种前馈补偿加PID反馈控制的自适应控制方案.由于在控制力矩中引入积分项,使操作器关节的跟踪精度和抗干扰能力得到提高.本文分析了摩擦干扰和执行机构的惯性对控制方案的影响.本文进一步的研究表明:在许多情况下,只需对操作器动力学中耦合和非线性最强的项进行补偿,然后加PID反馈控制,就能取得较好的控制效果.从而简化了控制方案,以PUMA560的前三个关节的参数作模型,对文中的方法进行了仿真.     

合成氨氢氮比控制的实现

讨论了合成氨过程中氢氮比控制的特点和方案，采用预测控制和PID相结合的控制方案，通过调节造气工段吹风段的回收时间来进行控制，达到了提高合成氨产量的目的。     

转子系统振动的灰色关联控制方法研究

将灰色关联控制理论应用于转子系统的振动主动控制,设计了转子系统振动的灰色关联控制方案．该方案依据转子工作曲线和实测曲线的关联度实现对转子振动的控制,因此不需要转子系统的精确的数学模型,具有建模迅速,控制及时、准确,便于工程实现等优点．将该方案应用于一带电磁阻尼器的单盘转子系统的振动主动控制中,仿真结果验证了该控制方法的有效性．     

离散时间非线性系统的数据驱动无模型自适应迭代学习控制

本文基于迭代域的动态线性化方法,提出了一类单入单出离散时间非线性系统的数据驱动无模型自适应迭代学习控制方案.无模型自适应迭代学习控制本质上属于一种数据驱动控制方法,仅利用被控对象的输入输出数据即可实现控制方案的设计.理论分析表明无模型自适应迭代学习控制方案可以保证最大学习误差的单调收敛性.数值仿真和快速路交通控制应用验证了无模型自适应迭代学习控制方案的有效性.     

纸浆浓度专家PID控制

本文简要的分析了普通PID控制的不足，在这一基础上介绍了专家PID控制的特点，并提出了一种新的控制方案——专家PID控制，通过与普通PID浓度控制曲线相比，该方案具有较好的动态性能和鲁棒性。     

基于控制性能的MIMO非线性系统动态面控制

针对一类不确定非线性MIMO(multiple-input multiple-output)系统,在动态面控制方法的基础上,提出了自适应跟踪控制方案.通过引入性能函数和输出误差转换,保证输出信号具有指定的跟踪速度、跟踪误差、最大超调量.为了避免控制奇异问题,采用神经网络直接逼近期望控制信号.该方案无需估计神经网络的权值,仅对1个参数进行自适应律设计.理论证明了闭环系统所有信号有界,仿真结果验证了所提方案的有效性.     

Realization of online optimizing control in an industrial semi-batch polymerization

In this work, the realization of an online optimizing control scheme for an industrial semi-batch polymerization reactor is discussed in detail. The goal of the work is the automatic minimization of the duration of the batch without violating the tight constraints for the product specification which translate into stringent temperature control requirements for a highly exothermic reaction. Crucial factors for a successful industrial implementation of the control scheme are the development and the validation of a process model that is suitable for process optimization purposes and the estimation of unmeasured process states and the online compensation of model uncertainties. Two implementations are proposed, a direct online optimizing control scheme and a simplified scheme that combines a model-predictive temperature controller and a monomer feed controller that steers the cooling power to a predefined value in a cascaded fashion. We show by simulation results with a validated process model that both schemes achieve the goals of tight temperature control and reduction of the batch time. The performance of the NMPC controller is superior, on the other hand the cascaded scheme could be directly implemented into the DCS of the plant and is in daily operation while the online optimizing scheme requires an additional computer and is currently in the test phase.     

Nonlinear model predictive control scheme for stabilizing annulus pressure during oil well drilling

This paper presents a nonlinear model predictive control scheme for stabilizing the well pressure during oil well drilling. While drilling, a fluid is pumped through the drill string and the drill bit, and is returning through the annulus between the drilled well and the drill string. Varying reservoir conditions and fluctuation in circulation flow rates cause sudden variations in the pressure conditions along the well. To compensate for these pressure fluctuations, the annulus choke valve opening can be adjusted. The proposed control scheme is based on a first-principles two-phase flow model using spatial discretization of the complete well. The optimal future choke settings are found using the Levenberg–Marquardt optimization algorithm. This control scheme is evaluated against two other control methods, a manual control scheme and a standard feed-back PI-control scheme of the choke valve with feed-forward control of the pump rates. The PI-control parameters are found using the Ziegler–Nichols closed-loop method based on simulations from a low-order model. The results show that both the PI-control scheme and the model predictive control scheme are superior to manual control. However, the PI-control scheme requires that the control parameters are re-designed when the operating conditions are deviating from the original design conditions. The model predictive control scheme will perform within the operating limits as long as the detailed model is able to describe the actual conditions of the well.     

一种新型的冗余机器人任务空间分散式自适应鲁棒控制方案

本文提出一种任务空间冗余机器人渐近最优分散式自适应鲁棒控制方案。它可以在线同时完成关节状态的轨迹规划与控制任务;并对系统的未知参数具有自适应能力;对参数失配,有界扰动以及系统控制与状态约束具有鲁棒性。     

DoS攻击下网络化控制系统基于观测器的记忆型事件触发预测控制

本文研究了DoS攻击下网络化控制系统记忆型事件触发预测补偿控制问题. 首先, 由于网络带宽资源有限 和系统状态不完全可观测性, 引入了记忆型事件触发函数, 为观测器提供离散事件触发传输方案. 然后, 分析了网络 传输通道上发生的DoS攻击. 结合上述记忆型事件触发方案, 在控制节点设计一类新颖的预测控制算法, 节省网络 带宽资源并主动补偿DoS攻击. 同时, 建立了基于观测器的记忆型事件触发预测控制的闭环系统, 并且分析稳定性. 通过线性矩阵不等式(LMI)和Lyapunov稳定性理论, 建立了控制器、观测器和记忆型事件触发矩阵的联合设计方案, 并验证了该方案的可行性. 仿真结果表明, 该方案结合记忆型事件触发机制可以有效补偿DoS攻击, 节约网络带宽 资源.     

Fast response and robust controller based on continuous eigenvalue configurations and time delay control

A soft variable structure point-to-point control scheme is proposed for a micro positioning system. The specific scheme is continuous eigenvalue configurations control combined with time delay control. By continuous tuning the state feedback control vector, the eigenvalues of the system will proceed continuously toward negative infinity, which will bring quick response. The simple tuning strategy is derived, which is a continuous function of displacement error. Furthermore, Time delay control is adopted to improve robustness to system uncertainties and disturbances. From the simulation and experimental results, the proposed control scheme provides good performances in settling time, positioning accuracy and disturbance rejection.     

Optimization control for the coordinated system of an ultra-supercritical unit based on stair-like predictive control algorithm

This study proposes an optimal control scheme for the coordinated control system (CCS) of an ultra-supercritical unit. This scheme utilizes a stair-like predictive control algorithm as the core to solve fundamentally the control problem of large delay and inertia in boiler combustion and integrates the feedforward and decoupling control concepts to preserve the traditional control experience. This study aims to provide technical support for the clean and efficient use of coal and the large-scale consumption of renewable energy sources in China. Non-real-time and real-time simulation results show that the scheme can achieve optimal control for each controlled variable, especially in the decoupling control mode; moreover, the fluctuation of each controlled variable is considerably reduced, and the adjustment of each control variable is stable, thereby improving the stability and anti-interference capability of the CCS. From the perspective of practical application of engineering, the research results have been directly productized and applied to practical engineering, the engineering application shows that the control performance is basically consistent with the simulation, the response rate of the unit is considerably increased, and the fluctuation of main steam pressure and mid-point temperature is considerably reduced. In this case, the proposed scheme can guarantee the safety, stability, economy, and flexibility of the unit operation.     

A model reference robust control with application to a flight control system design

In this paper, a new model reference robust control scheme for plants with relative degree greater than one is proposed for the purpose of coping with the “explosion of complexity” problem in control law design. The key of the scheme is that we use a first‐order filter to link each subsystem, so that the derivative of some nonlinear functions can be avoided. As a result, the final control law can be greatly simplified. The application of this scheme to a flight control system shows that both the tracking performance and the control effort can be improved significantly in comparison with earlier research. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

具有理想跟踪特性的鲁棒变结构模型参考自适应控制

针对相对阶为1的定常线性被控对象,提出了一种控制增益可切换的鲁棒变结构模 型参考自适应控制方案.该方案在对象参数及高频增益符号均未知的情形下,可确保跟踪误 差满足预先给定的过渡过程性能指标,即超调量、过渡过程时间和稳态误差.     

Fuzzy sliding mode control for a robot manipulator

This work presents the design of a robust control system using a sliding mode controller that incorporates a fuzzy control scheme. The presented control law superposes a sliding mode controller and a fuzzy logic controller. A fuzzy tuning scheme is employed to improve the performance of the control system. The proposed fuzzy sliding mode control (FSMC) scheme utilizes the complementary cooperation of the traditional sliding mode control (SMC) and the fuzzy logic control (FLC). In other words, the proposed control scheme has the advantages which it can guarantee the stability in the sense of Lyapunov function theory and can ameliorate the tracking errors, compared with the FLC and SMC, respectively. Simulation results for the trajectory tracking control of a two-link robot manipulator are presented to show the feasibility and robustness of the proposed control scheme. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008