基于DCS的三容水箱液位控制实验平台的研究

本课题以实验室教改项目为背景。该实验平台是将“三容水箱”为控制对象的实验装置和重点实验室“工业过程控制与仿真实验室”提供的Symphony分散控制系统连接起来而形成的闭环控制系统。可以模拟工业生产过程中的液位、流量等变量,并对这些变量进行控制、测量及观测。该综合实验平台具有强大的实验功能,能完成一阶及多阶对象。多输入-多输出解耦等实验;具有很好的人机界面功能。直观的显示出水箱液位。     

液晶自适应光学系统中控制矩阵的精度分析和优化

为了提高自适应光学系统的校正精度,提出了一种新的通过改变测量响应矩阵时的调制波长来准确计算控制矩阵的方法。首先,测量去除平移项的前35项Zernike模式在不同调制波长下的实际光波位相调制曲线。然后,对每个调制波长,依次计算相对于原点的位相调制曲线,最终将找到一个与实际光波位相调制曲线斜率相差最小的位相调制曲线。其所对应的调制波长,就是测量响应矩阵时,在相应的Zernike模式下应该施加在液晶波前校正器上的调制波长。这样,对于35个Zernike模式,便可以找到35个调制波长。最后,对于每个Zernike模式即响应矩阵的每一列对相应的调制波长进行归一化,最终得到准确的控制矩阵。实验表明,用此方法后,液晶自适应光学系统的校正精度由73%提高到了95%以上。校正误差为常规方法的1/5,且此比例系数与系统的最大畸变补偿位相的大小无关。此方法极大地提高了液晶自适应光学系统的校正精度。     

基于模型参考自适应控制的直线电机位置控制

针对直线电机的强非线性和时变特性,采用模型参考自适应控制(MRAC)方法对SISO直线电机闭环位置控制器进行了研究。利用偶极子对消建立了简化的永磁直线电机二阶数学模型,提出了基于局部参数最优化MIT(梯度)方案和全局稳定性理论的Lyapunov方案下的二阶直线电机位置模型参考自适应控制器,并对自适应控制器下的直线电机闭环系统稳定性进行了分析研究。在相同的前馈加反馈的控制器下,对这两种方案下的实验结果进行了对比分析。研究结果表明,基于Lyapunov第二方法设计的二阶控制器比MIT方法下的二阶控制器更能实现对三阶点到点轨迹输入信号的快速响应和跟踪,证实了直线电机位置自适应控制的有效性。     

Tracking control of cascade systems based on passivity: the nonadaptive and adaptive cases

A new cascade passivity-based control scheme for tracking purposes is proposed in this paper. The proposed scheme is valid for a certain class of nonlinear systems even with unstable zero dynamic, and it is also useful for regulation and stabilization purposes. The cases where all system parameters are assumed to be known (nonadaptive case) and also the case when they are unknown (adaptive case) are considered. Some simulation examples are studied to analyze the behavior of the proposed scheme.     

Internal model control structure using adaptive inverse control strategy

In this paper, we propose a new adaptive internal model control scheme based on adaptive finite impulse response filters. This scheme provides the same design procedure for both minimum and nonminimum phase plants. The plants under consideration may contain time delay. The tracking objective is accomplished for both invertible and noninvertible stable plants. The internal model of the plant and its inverse are estimated by recursive least-squares and least-mean-squares algorithms, respectively. The closed loop is designed such that the system from the reference input to the plant output can be approximately represented by a pure delay. The effect of the process zeros on the output is compensated by using adaptive finite impulse response filters. This avoids the cancellation of noncancellable zeros of the plant and forces the plant output to track the reference input with a delay. The stability of the closed loop for both minimum and nonminimum phase systems is guaranteed. Computer simulation and laboratory scale experimental results are included in the paper to demonstrate the effectiveness of the proposed method.     

汽车道路模拟系统的模糊自适应控制及仿真

以汽车道路模拟系统为研究对象,根据模糊控制理论,将模糊控制与常规的增量式PID控制相结合,设计出一套模糊自适应控制系统.并对C级路面谱进行仿真再现,仿真结果表明,该控制器比常规PID控制器具有更高的控制精度和更好的动态性能,在道路模拟仿真试验中可以达到非常满意的效果.     

智能自适应逆控制在无压式淬火机上的应用

将智能控制方法与自适应逆控制思想相结合用于无压式淬火机的综合自动控制．研究建立了基于智能自适应逆控制的终冷温度预测和控制模型，经现场实际验证表明，预测控制模型具有较高的预测精度和良好的控制效果。     

神经网络自适应控制的研究进展及展望

关于人工神经网络与自适应结合的研究,近年来已成为智能控制学科的热点之一。自适应具有强鲁棒性,神经网络则具有自学习功能和良好的容错能力,神经网络自适应控制由于较好地结合了二者的优点而具有强大的优势。本文系统地综述了神经网络自适应控制的进展,讨论了神经网络自适应的主要模型和算法,并就其存在的一些问题、应用与发展趋势进行了探讨。     

一种新的自适应PID控制算法

针对大惯性工业对象，设计了一种新的自适应PID调节器控制算法并应用手工业温度控制系统中，实验结果表明，利用人工智能算法与PID自适应算法的有机结合，可以使温度控制曲线在不同的阶段平滑过渡，使系统控制过程达到最优。     

A comparison of traditional and adaptive control strategies for systems with time delay

A recently developed tuning method is compared to an adaptive Smith Predictor control strategy. The robustness of each method is considered for time-varying plant parameters. Examples with simulations are provided to compare the methods and present conclusions on the advantages and disadvantages of each.     

水位智能控制的实现

仿人工智能控制算法在大惯性、纯滞后系统中的应用,可克服传统PID控制的相位滞后、积分饱和,解决控制系统的稳定性及准确性的矛盾。将该控制算法应用到水位控制,取得了较好的控制效果。     

Model reference adaptive control for a piezo-positioning system

Piezoelectric (PZT) actuators having the characteristic of infinitely small displacement resolution are popularly applied as actuators in precision positioning systems. Due to its nonlinear hysteresis effect, the tracking control accuracy of the precision positioning system is difficultly achieved. Hence, it is desirable to take hysteresis effect into consideration for improving the trajectory tracking performance. In this paper, a model reference adaptive control scheme based on hyperstability theory is developed for a moving stage system driven by a PZT actuator. It is worth emphasizing that the controller can be constructed without a nonlinear hysteresis dynamic equation to compensate the hysteresis effect. According to simulation results, the tracking error was only nanometer order. Through experimental examinations, the tracking performance was obtained as precision as ten nanometers order which is the resolution limitation of the measurement system. The effectiveness of the proposed adaptive control scheme was validated.     

自适应逆控制原理应用于高精度恒流源

将自适应逆控制理论应用于高精度恒流源的设计,系统结构简单,易于实现。实验结果表明,采用自适应逆控制的方法能够使输出电流具有很高的精度和稳定性,可实际应用于仪器仪表、家用电器、传感技术和通信设备等领域。     

Real-time tracking control of electro-hydraulic force servo systems using offline feedback control and adaptive control

This paper focuses on an application of an electro-hydraulic force tracking controller combined with an offline designed feedback controller (ODFC) and an online adaptive compensator in order to improve force tracking performance of an electro-hydraulic force servo system (EHFS). A proportional-integral controller has been employed and a parameter-based force closed-loop transfer function of the EHFS is identified by a continuous system identification algorithm. By taking the identified system model as a nominal plant model, an H_∞ offline design method is employed to establish an optimized feedback controller with consideration of the performance, control efforts, and robustness of the EHFS. In order to overcome the disadvantage of the offline designed controller and cope with the varying dynamics of the EHFS, an online adaptive compensator with a normalized least-mean-square algorithm is cascaded to the force closed-loop system of the EHFS compensated by the ODFC. Some comparative experiments are carried out on a real-time EHFS using an xPC rapid prototype technology, and the proposed controller yields a better force tracking performance improvement.     

Observer-based adaptive fuzzy-neural control for a class of uncertain nonlinear systems with unknown dead-zone input

Based on the universal approximation property of the fuzzy-neural networks, an adaptive fuzzy-neural observer design algorithm is studied for a class of nonlinear SISO systems with both a completely unknown function and an unknown dead-zone input. The fuzzy-neural networks are used to approximate the unknown nonlinear function. Because it is assumed that the system states are unmeasured, an observer needs to be designed to estimate those unmeasured states. In the previous works with the observer design based on the universal approximator, when the dead-zone input appears it is ignored and the stability of the closed-loop system will be affected. In this paper, the proposed algorithm overcomes the affections of dead-zone input for the stability of the systems. Moreover, the dead-zone parameters are assumed to be unknown and will be adjusted adaptively as well as the sign function being introduced to compensate the dead-zone. With the aid of the Lyapunov analysis method, the stability of the closed-loop system is proven. A simulation example is provided to illustrate the feasibility of the control algorithm presented in this paper.     

基于自调整模糊控制的汽车ABS路面识别

在基于滑移率的变路面汽车ABS模糊控制中,针对滑移率偏差及其变化率在路面识别过程中会发生较大的跳变,导致模糊控制的输入量超过其论域范围,制动压力调节较长时间失效的情况,提出了一种自调整模糊控制算法。该控制算法与常规的模糊控制算法相比,能够自动调节比例系数,使过大的滑移率偏差及其变化率尽快回到模糊控制输入量的论域范围内,更好地进行压力调节,从而将滑移率尽早的控制在最佳滑移率附近,减少制动时间和制动距离。     

An adaptive agile manufacturing control infrastructure based on TOPNs-CS modelling

In this paper, an infrastructure for adaptive production control in an agile manufacturing environment is proposed. With this infrastructure, Virtual Production Systems (VPSs), each of which takes care of the production of a specific customer ordered product, can be dynamically and flexibly constructed. This can be achieved logically by product workflow and physically by the resources in one or more manufacturing systems, e.g. job shops. To respond to changes and disturbances to a VPS, architecture for the adaptive controller of a VPS is designed based on adaptive control principles and Temporised Object-Oriented Petri Nets with Changeable Structure (OPNs-CS) modelling. A case study is used in this paper to illustrate how adaptive production control of VPS functions can be conducted to cope with changes and disturbances to the production system.     

Multilevel adaptive control of nonlinear interconnected systems

This paper presents an adaptive backstepping-based multilevel approach for the first time to control nonlinear interconnected systems with unknown parameters. The system consists of a nonlinear controller at the first level to neutralize the interaction terms, and some adaptive controllers at the second level, in which the gains are optimally tuned using genetic algorithm. The presented scheme can be used in systems with strong couplings where completely ignoring the interactions leads to problems in performance or stability. In order to test the suitability of the method, two case studies are provided: the uncertain double and triple coupled inverted pendulums connected by springs with unknown parameters. The simulation results show that the method is capable of controlling the system effectively, in both regulation and tracking tasks.     

Fuzzy-nets-based in-process surface roughness adaptive control system in end-milling operations

A fuzzy-nets-based in-process adaptive surface roughness control (FN-ASRC) system was developed to be able to adapt cutting parameters in-process and in a real time fashion to improve the surface roughness of machined parts when the surface roughness quality was not meeting customer requirements in the end-milling operations. The FN-ASRC system was comprised of two sub-systems: (1) fuzzy-nets in-process surface roughness recognition (FN-IPSRR); and (2) fuzzy-nets adaptive feed rate control (FN-AFRC) sub-system. To test the system, while the machining process was taking place, the FN-IPSRR system predicted the surface roughness, which was then compared to the desired surface roughness. If the desired surface roughness was not met, then, the FN-AFRC system proposed a new feed rate for the machining process. Once the feed rate was changed, and the cutting continued, the output of the surface roughness of the new feed rate was compared with the desired surface roughness. This proposed FN-ASRC system has been demonstrated to be successful using 25 experimental tests with 100% success rate.