无人直升机自抗扰自适应轨迹跟踪混合控制

为满足无人直升机高精度轨迹跟踪的控制需求,并降低直升机动力学模型误差对飞行控制器飞行控制效果产生的影响,提出自抗扰自适应直升机混合控制.该控制器的内环控制采用模型跟随自适应控制,通过使用动量反向传播算法(MOBP)对该内环控制参数进行实时优化.通过使用自抗扰控制(ADRC)对直升机的水平速度进行控制.仿真结果表明,该混合控制器能够实现直升机对预定轨迹的跟踪.相对PID和级联ADRC控制,该控制器具有更好的抗扰性和鲁棒性.通过在200 kg级的专业植保无人直升机XV-2上搭载所提出的控制器,使其自主飞行轨迹跟踪控制的均方根误差在0.6 m以内.     

Tuning of Robust Distant Downstream PI Controllers for an Irrigation Canal Pool. II: Implementation Issues

Based on the companion paper results, this paper presents a robust tuning method to tune a proportional integral (PI) controller that fulfills the design requirements for a single pool with different hydraulic conditions. The robust PI controller parameters are obtained analytically as a function of the physical parameters of the canal pool. Important implementation issues are also considered. Rules are provided for the sampling time selection in order to recover the continuous-time performance. When the sampling time is imposed, it has to be included in the controller design, by modifying the delay of the system. A simple way is proposed to take account of the gate opening as control action variable, instead of the upstream discharge. This robust PI tuning method is evaluated by simulation on a full nonlinear model of two different canal pools for different flow conditions and different implementations: continuous-time control, discrete-time control, using the discharge or the gate opening as control action variable. Simulation results show that the method leads to efficient realistic PI controllers for a canal pool.     

球磨机制粉系统的线性自抗扰控制

球磨机制粉系统具有大惯性、大时滞和强耦合等特点,很难建立精确的数学模型.本文分析了球磨机制粉系统的动态特性,并为其设计分散线性自抗扰控制方案.该方案综合分散控制和线性自抗扰控制器的优点,结构简单,不依赖于对象精确模型,可以对被控对象中存在的耦合、干扰和不确定性等进行估计并补偿.根据实际现场要求,对球磨机制粉系统进行设定值跟踪实验、输入扰动实验和性能鲁棒性实验,并比较所设计方案与PID方案的控制性能.结果表明,分散线性自抗扰控制具有更强的解耦能力和抗干扰能力,且性能鲁棒性更优.     

Adaptive Learning with Large Variability of Teaching Signals for Neural Networks and Its Application to Motion Control of an Industrial Robot

Recently, various control methods represented by proportional-integral-derivative (PID) control are used for robotic control.To cope with the requirements for high response and precision, advanced feedforward controllers such as gravity compensator,Coriolis/centrifugal force compensator and friction compensators have been built in the controller.Generally, it causes heavy computational load when calculating the compensating value within a short sampling period.In this paper, integrated recurrent neural networks are applied as a feedforward controller for PUMA560 manipulator.The feedforward controller works instead of gravity and Coriolis/centrifugal force compcusators.In the learning process of the neural network by using back propagation algorithm, the learning coefficient and gain of sigmoid function are tuned intuitively and empirically according to teaching signals.The tuning is complicated because it is being conducted by trial and error.Especially, when the scale of teaching signal is large, the problem becomes crucial.To cope with the problcm which concerns the learning performance, a simple and adaptive learning technique for large scale teaching signals is proposed.The learning techniques and control effectiveness are evaluated through simulations using the dynamic model of PUMA560 manipulator.     

Adaptive PID control system for an autonomous underwater vehicle

The control system of an autonomous underwater vehicle (AUV) is introduced. According to the control requirements of the AUV, a simple but practical adaptive PID control method is de- signed. The semi-physical simulation is done to test the feasibility of the control system. The neural network idea and the structure of PID controller are referred to design the adaptive PID controller. An intelligent integral is introduced to improve control precision. Compaed with traditional PID con- trollers, the adaptive PID controller has simple structure, good online adjusting ability, fast conver- gence and good robustness. The simulation experiments also show that the adaptive PID control sys- tem has high precision and fine antijamming ability.     

一类不确定非线性系统的串级主动补偿控制

针对一类具有下三角结构的单输入单输出不确定非线性系统,研究其稳定控制问题.提出一种结构简单、收敛速度可控以及抗扰性能良好的基于Backstepping方法的串级主动补偿控制策略,实现了闭环系统的渐近稳定控制.为解决闭环系统中不确定非线性未知问题,设计一种新的观测器,使得这种观测器能够实时跟踪闭环系统的不确定非线性.通过引入奇异扰动性理论,给出了闭环系统稳定性分析.仿真实验结果验证了该控制方法的有效性.     

基于非线性模型预测控制的自动泊车路径跟踪

与行驶速度较高的其他无人驾驶工况相比, 自动泊车时参考路径的曲率较大, 因此车辆转向轮转角速度的限制等系统约束条件会严重影响自动泊车路径跟踪控制器的性能. 为了解决这一问题, 提出了基于非线性模型预测控制的自动泊车路径跟踪控制器, 并在MATLAB/Simulink和PreScan联合仿真环境中将该控制器与基于线性时变模型预测控制的控制器进行了对比. 仿真结果表明非线性模型预测控制器可以实现多约束条件下的自动泊车, 泊车完成后车辆航向与车位中线的夹角为0.0189 rad, 车辆后桥中点与车位中线的距离为0.1045 m, 仅为车身宽度的5.56%. 相比线性时变模型预测控制器, 非线性模型预测控制器具有泊车精度更高、安全裕度更大、泊车耗时更少等优势. 在实时性方面, 该控制器也能够满足自动泊车的需求.      

基于模糊神经元PID解耦的精馏塔温度控制

针对精馏塔温度控制这个非线性耦合对象,提出了一种模糊神经元解耦智能控制器。该控制器避免了精馏塔精确数学模型的推导和严格计算解耦算式的麻烦,是模糊逻辑控制与神经元PID控制器的结合。同时,分析了控制器的结构及其学习算法。通过仿真试验,得到了较为理想的控制效果。     

Application of Fuzzy Logic Controller to Level Control of Twin-Roll Strip Casting

SymbolList　　D———Stripthickness ;　　E———Levelerror ;　　ΔE———Changeoflevelerror ;　　H———Moltensteellevel;　　L———Widthofcastingroll;　　Q———Volumeofmoltensteel;　　R———Radiusofcastingroll;　　S———Lateralareaofmoltensteelpool;　　u ,u1 ,u2 ———Outputofintelligentfuzzylogiccontrol ler,fuzzylogiccontrollerandPIDcon troller ;　　v———Castingspeed ;　　α———Proportionfactor ;　　τ———Time .　　Thetwin rollstripcastingprocessisanewstripproductionmethod …     

Active Control of Cross Wind Response of 76-Story Tall Building Using a Fuzzy Controller

This paper focuses on the benchmark problem application regarding the vibration control of tall buildings under cross wind excitation. The building under consideration is the 76-story, 306-m tall reinforced concrete office tower proposed for the city of Melbourne, Australia. The adopted control scheme consists of an active tuned mass damper (ATMD) where the control action is achieved by a fuzzy logic controller (FLC). The main advantage of the FLC is its inherent robustness and ability to handle any nonlinear behavior of the structure and the fact that its implementation does not require a mathematical model of the structure. This benchmark study is based on specified design constraints for the ATMD to be considered in the design of the proposed control scheme. The performance of the controller has been demonstrated through the uncertainty in stiffness (+15 and ?15% variation from initial stiffness) of the building. The results of the simulation show a good performance by the fuzzy controller for all cases tested. Also the results show that the fuzzy controller performance is similar to the linear quadratic Gaussian (LQG) controller, while possessing several advantages over the LQG controller.     

Robust Control of Spacecraft Formation Flying

In this paper, a robust control scheme for two spacecraft in formation subjected to time-variant external disturbances in the space environment was developed. The proposed controller consists of two parts, the first part is for the nominal system without disturbances and the second part is to compensate for effects of system disturbances. A dynamic relative motion error model was established to design the second part of the controller and to analyze the stability of the closed-loop system using Lyapunov stability theory. Furthermore, the robustness of proposed control method to the system disturbances is analyzed based on robust control theory. It is proven that the relative motion error of two spacecraft in formation is uniformly ultimately bounded under the proposed controller for the assumed disturbances in the dynamic model.     

带有负载观测的异步电动机广义预测控制

提出了一种带有负载观测功能的异步电动机广义预测控制算法,在对系统动态模型分析的基础上建立了调速系统的受控自回归积分滑动平均模型.该控制算法给出了能够使下一次采样时刻的实际转速以最优特性跟踪下一时刻参考转速的广义预测控制律,并采用负载转矩观测器的前馈功能增强速度控制的抗干扰能力.仿真和实验结果表明,通过合理选择控制器参数,具有转矩预测功能的直接转矩控制系统在转速跟踪和抗扰能力方面得到一定提高.     

结晶器液压伺服振动装置的神经元自适应PID控制

针对结晶器液压振动装置的特点,利用神经元的自学习功能构成自适应ＰＩＤ控制器,应用该控制器对结晶器振动装置的液压伺服系统进行控制研究,并给出了设计方法。仿真结果表明,该控制器无需对系统进行建模,它不仅结构简单,而且具有良好的动态性能和较强的鲁棒性和自适应性,易于现场应用。     

Optimal Control Method for Seismically Excited Building Structures with Time-delay in Control

Optimal control method for seismic-excited linear structures with time delay in control is investigated in this paper. Using zero-order holder, the continuous time differential equation with time delay can be transformed into a standard discrete time form that contains no time delay in terms of two cases that the time delay is integer and noninteger times of sampling period, respectively. The continuous time performance index is used in the design of the optimal controller and it is also transformed into discrete form. Then, the optimal controller can be designed according to the classical discrete LQR method. The controller obtained contains not only current step of state feedback but also a linear combination of some former steps of control. Because the optimal controller is obtained directly from the time-delay differential equation, it is prone to guarantee the stability of the controlled structures. Furthermore, this control method is available for case of large time delay. The performance of the control method proposed and system stability are both demonstrated by numerical simulation results. Simulation results demonstrate that the control method proposed in this paper is a viable and attractive control strategy for application to seismically excited linear structures.     

基于时变局部模型的无人驾驶车辆路径跟踪

目前常用于无人驾驶车辆路径跟踪控制的有模型控制方法有两类,一类是基于全局模型的控制方法,另一类是基于局部模型的控制方法。基于全局模型的路径跟踪控制中无人驾驶车辆的纵向速度与全局坐标系中的横向、纵向位移误差之间存在随航向角变化的耦合关系,这种耦合关系使得控制器无法将纵向速度作为控制输入来提高路径跟踪控制的精确性。基于局部模型的路径跟踪控制器通常采用误差模型作为参考模型,这种模型使得控制器在参考路径曲率变化幅度较大时精确性较低。针对前述问题,基于非线性模型预测控制滚动优化的原理,提出一种基于时变局部模型的无人驾驶车辆路径跟踪控制方法,并在低速高附着路面、低速低附着路面和高速低附着路面等工况下进行仿真验证。在仿真结果中,相比于基于全局模型的路径跟踪控制器、基于局部模型的路径跟踪控制器以及Stanley路径跟踪控制器,基于时变局部模型的路径跟踪控制器精确性更高,其位移误差绝对值不超过0.3342 m,航向误差绝对值不超过0.0913 rad。      

面向可持续发展的半导体制造的集成产品和过程控制

Semiconductor fabrication is a manufacturing sequence with hundreds of sophisticated unit operations and it is always challenged by strategy development for ensuring the yield of defect-free products. In this paper, an advanced control strategy through integrating product and process control is established. The proposed multiscale scheme contains three layers for coordinated equipment control, process control and product quality control. In the upper layer, online control performance assessment is applied to reduce the quality variation and maximize the overall product performance (OPP). It serves as supervisory control to update the recipe of the process controller in the middle layer. The process controller is designed as an exponentially weighted moving average (EWMA) run-to-run controller to reject disturbances, such as process shift, drift and tool worn out, that are exerted to the operation. The equipment in the process is individually controlled to maintain its optimal operational status and maximize the overall equipment effectiveness (OEE), based on the set point given by the process controller. The efficacy of the proposed integrated control scheme is demonstrated through case studies, where both the OPP (for product) and the OEE (for equipment) are enhanced.     

Multiscale Wavelet-LQR Controller for Linear Time Varying Systems

This paper proposes a multiresolution based wavelet controller for the control of linear time varying systems consisting of a time invariant component and a component with zero mean slowly time varying parameters. The real time discrete wavelet transform controller is based on a time interval from the initial until the current time and is updated at regular time steps. By casting a modified optimal control problem in a linear quadratic regulator (LQR) form constrained to a band of frequency in the wavelet domain, frequency band dependent control gain matrices are obtained. The weighting matrices are varied for different bands of frequencies depending on the emphasis to be placed on the response energy or the control effort in minimizing the cost functional, for the particular band of frequency leading to frequency dependent gains. The frequency dependent control gain matrices of the developed controller are applied to multiresolution analysis (MRA) based filtered time signals obtained until the current time. The use of MRA ensures perfect decomposition to obtain filtered time signals over the finite interval considered, with a fast numerical implementation for control application. The proposed controller developed using the Daubechies wavelet is shown to work effectively for the control of free and forced vibration (both under harmonic and random excitations) responses of linear time varying single-degree-of-freedom and multidegree-of-freedom systems. Even for the cases where the conventional LQR or addition of viscous damping fails to control the vibration response, the proposed controller effectively suppresses the instabilities in the linear time varying systems.     

Simple Optimal Downstream Feedback Canal Controllers: Theory

A new class of downstream water-level feedback controllers is proposed that can vary from a series of individual proportional-integral (PI) controllers (each gate adjusted based on one water level) to fully centralized controllers (each gate adjusted based on all water levels) that include the effects of lag time. The controller design method uses discrete-time state-feedback control with a quadratic penalty function, physically based states, and no state estimation. A simple, linear model of canal pool response, the integrator-delay model, is used to define the state transitions. All controllers within this class are tuned for the entire canal using optimization techniques. This avoids the tedious task of manually tuning simple controllers. The relative performance of the various controllers within this class can be directly compared without simulation, since the same objective function is used to tune each controller. An example is provided which suggests that the fully centralized controller will perform better than a series of local controllers. However, reasonably good performance can be obtained for some intermediate PI controllers that pass information to one additional check structure upstream and downstream. This should limit some of the difficulties reported for full optimal controllers where all check structures respond to water-level errors in all pools (e.g., saturation of inputs). The results of simulation studies of these controllers are provided in a companion paper.     

基于自适应反步法的干扰补偿挖泥船动力定位控制

为解决挖泥船在挖泥强反作用干扰或恶劣环境干扰下,动力定位控制系统不稳定的难题,提出采用自适应反步法来解决挖泥船的动力定位问题.由于自适应算法采用实时估计干扰值并进行前馈补偿,而不是在挖泥机构上额外加装传感器的方法,从而简化了控制机构并同时保证了控制的效果.自适应控制能前馈补偿反作用干扰及环境干扰对船体的作用,使船体能以最小的误差与冲击稳定在指定位置.定位控制在强干扰作用下依然能快速跟踪设定位置,而且保证控制系统全局渐近稳定.仿真结果表明,动力定位系统在强干扰环境中依然能够保持良好跟踪的动静态性能.     

General Approach for Training Back-Propagation Neural Networks in Vibration Control of Multidegree-of-Freedom Structures

A general approach is proposed for back-propagation training of multilayer feed-forward (MLFF) neural networks for active control of earthquake-induced vibrations in multidegree-of-freedom structures. The training functions for adjustment of connection weights of the neural network controller are formulated in the proposed approach by minimizing a general cost function using the steepest gradient descent scheme. The proposed method can be applied for training an MLFF neural network controller in vibration control of building structures both in the pattern (online) and batch (off-line) mode. The method can be implemented in structural control systems with more than one control action. Case studies are presented to demonstrate the feasibility of implementing the training approach for effective vibration control of structures subjected to earthquake ground motions.