Dynamics and adaptive control of a dual-arm space robot with closed-loop constraints and uncertain inertial parameters

A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.

Application of Single Neuron Adaptive PID Regulators with Auto-tuning Gain in Industrial Parameter(Pressure)Closed-loop Process Control Systems

A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of induStrial parameter closed-loop process controlsystems is improved, and the work quality of the systems bettered.

Adaptive Robust Control for a Class of Uncertain MIMO Non-affine Nonlinear Systems

In this paper, the adaptive robust tracking control scheme is proposed for a class of multi-input and multi-output (MIMO) non-affine systems with uncertain structure and parameters, unknown control direction and unknown external disturbance based on backstepping technique. The MIMO non-affine system is first transformed into a time-varying system with strict feedback structure using the mean value theorem, and then the bounded time-varying parameters are estimated by adaptive algorithms with projection. To handle the possible 'controller singularity' problem caused by unknown control direction, a Nussbaum function is employed, and the dynamic surface control (DSC) method is applied to solve the problem of 'explosion of complexity' in backstepping control. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through Lyapunov stability theorem and decoupled backstepping method. Simulation results are presented to illustrate the effectiveness of the proposed control scheme. © 2014 Chinese Association of Automation.

Adaptive Robust Control for A Class of Nonlinear Systems with Unknown Uncertainties

The problem of robust stabilization for nonlinear systems with partially known uncertainties is considered in this paper. The required information about uncertainties in the system is merely that the uncertainties are bounded, but the upper bounds are incompletely known. This paper can be viewed as an extension of the work in reference [1]. To compensate the uncertainties, an adaptive robust controller based on Lyapunov method is proposed and the design algorithm is also suggested. Compared with some previous controllers which can only ensure ultimate uniform boundedness of the systems, the controller given in the paper can make sure that the obtained closed-loop system is asymptotically stable in the large. Simulations show that the method presented is available and effective.

Indirect Adaptive Fuzzy Output Feedback Control with Supervisory Controller for Uncertain Nonlinear Systems

In this paper, an indirect adaptive fuzzy output feedback controller with supervisory mode for a class of unknown nonlinear systems is developed. The proposed approach does not need the availability of the state variables, moreover, a supervisory controller is appended to the adaptive fuzzy controller to force the state to be within the constraint set. Therefore, if the adaptive fuzzy controller cannot maintain the stability, the supervisory controller starts to work to guarantee stability. On the other hand, if the adaptive fuzzy controller works well, the supervisory controller will be de-activated. The overall adaptive fuzzy control scheme guarantees the stability of the whole closed-loop systems. The simulation results confirm the effectiveness of the proposed method.

Model Reference Adaptive Control for Switched Systems with Closed-loop Reference Model Under Arbitrary Switching

This paper explores the model reference adaptive control problem for a class of switched linear systems under arbitrary switching with no need for the measurability of the system state.Based on the state of reference model and the measurable output error, adaptive laws and controllers are designed for switched systems.Each subsystem may have its individual reference model and controller, which increases the design flexibility.The introduction of the closed-loop reference model is to get a better transient performance of the whole switched systems.A numerical example is provided to verify the effectiveness of the main results.

Joint Closed-Loop Power Control and Adaptive Beamforming for Wireless Networks with Antenna Arrays in a 2D Urban Environment

The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to decrease the interference in wireless communication networks. In this paper, we propose smart step closed-loop power control (SSPC) algorithm in wireless networks in a 2D urban environment with constrained least mean squared (CLMS) algorithm. This algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. Also, we present switched-beam (SB) technique for enhancing signal to interference plus noise ratio (SINR) in wireless networks. Also, we study an analytical approach for the evaluation of the impact of power control error (PCE) on wireless networks in a 2D urban environment. The simulation results indicate that the convergence speed of the SSPC algorithm is faster than other algorithms. Also, we observe that significant saving in total transmit power (TTP) are possible with our proposed algorithm. Finally, we discuss three parameters of the PCE, number of antenna elements, and path-loss exponent and their effects on capacity of the system via some computer simulations.

Design of Type-1 and Interval Type-2 Fuzzy PID Control for Anesthesia Using Genetic Algorithms

This paper presents the automatic drug administration for the regulation of bispectral (BIS) index in the anesthesia process during the clinical surgery by controlling the concentration target of two drugs, namely, propofol and remifentanil. To realize the automatic drug administration, real clinical data are collected for 42 patients for the construction of patients’ models consisting of pharmacokinetic and pharmacodynamic models describing the dynamics reacting to the input drugs. A nominal anesthesia model is obtained by taking the average of 42 patients’ models for the design of control scheme. Three PID controllers are employed, namely linear PID controller, type-1 (T1) fuzzy PID controller and interval type-2 (IT2) fuzzy PID controller, to regulate the BIS index using the nominal patient’s model. The PID gains and membership functions are obtained using genetic algorithm (GA) by minimizing a cost function measuring the control performance. The best trained PID controllers are tested under different scenarios and compared in terms of control performance. Simulation results show that the IT2 fuzzy PID controller offers the best control strategy regulating the BIS index while the T1 fuzzy PID controller comes the second.

Interference Management for DS-CDMA Systems through Closed-Loop Power Control, Base Station Assignment, and Beamforming

In this paper, we propose a smart step closed-loop power control (SSPC) algorithm and a base station assignment method based on minimizing the transmitter power (BSA-MTP) technique in a direct sequence-code division multiple access (DS-CDMA) receiver with frequency-selective Rayleigh fading. This receiver consists of three stages. In the first stage, with constrained least mean squared (CLMS) algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference (IPI) is reduced in other paths in each RAKE finger. Also in this stage, the multiple access interference (MAI) from other users is reduced. Thus, the matched filter (MF) can use for more reduction of the IPI and MAI in each RAKE finger in the second stage. Also in the third stage, the output signals from the matched filters are combined according to the conventional maximal ratio combining (MRC) principle and then are fed into the decision circuit of the desired user. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can significantly reduce the network bit error rate (BER) compared to the other methods. Also, we observe that significant savings in total transmit power (TTP) are possible with our methods.

NONLINEAR STABLE ADAPTIVE CONTROL BASED UPON ELMAN NETWORKS

Elman networks' dynamical modeling capability is discussed in this paper firstly.According to Elman networks' unique structure,a weight training algorithm is designed and a nonlinear adaptive controller is constructed.Without the PE presumption,neural networks controller's closed loop properties are studied and the whole Elman networks' passivity is demonstrated.

Multivariable Adaptive Decoupling Controller Using Hierarchical Multiple Models

To solve the problem such as too many models, long computing time and so on, a hierarchical multiple models direct adaptive decoupling controller is designed. It consists of multiple levels. In the upper level, the best model is chosen according to the switching index. Then multiple fixed models are constructed on line to cover the region which the above chosen fixed model lies in.In the last level, one free-running and one re-initialized adaptive model are added to guarantee the stability and improve the transient response. By selection of the weighting polynomial matrix, it not only eliminates the steady output error and places the poles of the closed loop system arbitrarily, but also decouples the system dynamically. At last, for this multiple models switching system, global convergence is obtained under common assumptions. Compared with the conventional multiple models adaptive controller, it reduces the number of the fixed models greatly. If the same number of the fixed models is used, the system transient response and decoupling result are improved. The simulation example illustrates the power of the derived controller.

A Fuzzy Controller for Blood Glucose-Insulin System

Diabetes therapy is normally based on discrete insulin infusion that uses long-time interval measurements. Nevertheless, in this paper, a continuous drug infusion closed-loop control system was proposed to avoid the traditional discrete approaches by automating diabetes therapy. Based on a continuous insulin injection model, two controllers were designed to deal with this plant. The controllers designed in this paper are: proportional integral derivative (PID), and fuzzy logic controllers (FLC). Simulation results have illustrated that the fuzzy logic controller outperformed the PID controller. These results were based on serious disturbances to glucose, such as exercise, delay or noise in glucose sensor and nutrition mixed meal absorption at meal time.

基于模糊PID控制的粉碎机转速和位置自适应控制研究

为提高粉碎机的控制性能,提出一种基于模糊PID控制的粉碎机转速和位置自适应控制算法。方法以粉碎机STM86步进电机控制为研究对象,构建粉碎机驱动电机数学模型,并结合PID控制和模糊控制设计基于模糊PID控制算法,以实现粉碎机的自适应控制。结果表明,模糊PID控制算法对粉碎机速度和位置控制的超调量分别为4.20%和0.13%,调节时间分别为0.21 s和0.02 s、平均跟随误差分别为0.02 mm和0.01 r/min;相较于PID控制、模糊滑模控制、模糊自抗干扰控制算法,模糊PID控制算法具有更低的超调量,更短的调节时间和更小的平均跟随误差。由此得出,模糊PID控制方法可实现更优异的粉碎机自适应控制,且具有一定的实际应用价值。

基于双环自适应滑模控制的高速列车运行追踪

针对列车高速运行跟踪控制问题,提出了一种基于双环结构的RBF神经网络自适应滑模控制算法。首先系统结构分为位移与速度控制子系统,防止列车因单个控制器故障而失控;在此基础上采用积分滑模控制,加强控制器的鲁棒性;同时在速度子系统中引入参数自适应算法与RBF神经网络自适应算法削弱列车受到基本阻力、附加阻力以及不确定性阻力带来的影响;最后通过Lyapunov稳定性分析证明系统的稳定性。通过仿真实验结果表明,位移误差在[-3.3×10^(-4),1.9×10^(-4)]范围以内,速度误差在[-2.1×10^(-2),3.1×10^(-2)]范围以内,该算法可以实现对列车的速度与位移精确追踪。

变排量液压马达旋转驱动系统角位移控制技术

变排量液压马达旋转驱动系统具有效率高、响应快、高负载匹配性、低功率需求等优势,能够大幅提高飞机液压旋转驱动系统的效率。为实现对变排量液压马达旋转驱动系统的精确控制,需开展系统角位移控制技术研究。建立了系统的数学模型,搭建了AMESim仿真模型,分析了系统的运动特性及频域控制特性,提出了由排量回路、转速回路和角位移回路组成的三闭环串级控制方案,研究了不同控制参数对系统控制特性的影响。研究结果表明,双闭环控制无法满足旋转驱动系统的稳定条件,三闭环控制引入转速负反馈克服了双闭环控制中角位移对转速的正反馈效应,增大了位置回路的阻尼,能实现系统稳定控制。同时研制了原理样机并进行了测试验证,测试数据表明,三闭环控制方案能实现旋转驱动系统高精度位置控制,为变量马达在飞机液压旋转驱动系统中的应用提供了参考。

难变形合金用轧辊感应加热温度控制策略及温辊轧制实验

针对轧辊电磁感应加热温度控制方法展开研究,开发了轧辊温度控制策略,调控轧辊辊面工作区温度。通过DEFORM模拟轧辊感应加热过程辨识轧辊感应加热数学模型参数,结合自适应模糊PID控制算法使用Simulink进行控制器的搭建与仿真,并进行轧辊静态局部感应加热温度调控实验验证。结果表明,辊面温度围绕目标温度值小幅振荡,温度控制过程无超调,预设温度550℃时最大误差小于25℃。最后与传统包套轧制工艺进行对比,分析温辊轧制Ti/Ti Al复合板的显微组织,结果表明温辊轧制工艺使Ti Al侧具有更细小的晶粒尺寸,界面区域宽度为75μm,通过轧辊加热和减小包套厚度使界面宽度减小25%。

基于自适应反步法的直驱式泵控液压系统控制策略

在闭式泵控伺服系统位置输出控制过程中,会出现非对称缸建模难、参数不确定性和控制算法调试困难等问题,为此,提出了一种自适应反步法控制策略(控制器),并采用半实物仿真平台对其可行性进行了验证。首先,推导了考虑单向阀和溢流阀的直驱式泵控非对称缸液压系统的数学模型;其次,采取引入向量的方式,将数学模型变成了严格反馈形式,以此设计了新的自适应反步法控制器,解决了参数不确定问题;最后,在Linux+Preempt-RT半实物仿真平台下,完成了直驱式泵控非对称缸位置系统自适应反步法控制的阶跃信号、正弦信号和加入时变负载的正弦信号试验,并将其控制结果与传统PID控制结果进行了对比分析。研究结果表明:采用自适应反步法的控制器的稳态精度可以达到±3.98 mm,相比PID的控制精度提高了53.6%;同时,在系统位置控制过程中,采用参数自适应律对系统的不确定性参数进行实时调整估计,可以呈现出良好的自适应动态逼近过程。该自适应反步法控制策略具有良好的跟踪性能和鲁棒性。

前级可变车载充电机双闭环区间二型模糊控制研究

现有车载充电机拓扑结构无法兼顾单相和三相交流电,控制策略难以实现宽范围电压的动态调节和高精度、低抖动的输出。针对上述问题,提出一种双闭环区间二型模糊控制的前级可变车载充电机。在图腾柱功率因数校正电路结构上,增加第三桥臂和对应的控制开关,设计出前级可变电路;选用LLC谐振电路作为车载充电机的后级电路。基于此拓扑,提出区间二型模糊电压外环和区间二型模糊电流内环的双闭环控制策略。经仿真分析验证了所提拓扑结构能够兼容两种规格交流电的可行性。同时,所提控制策略的系统输出与电压外环电流内环的双闭环PID和一型模糊双闭环PID相比,有了明显改善。

基于模糊自适应PI的伺服控制系统设计

本文分析了伺服控制三闭环调速的特点,介绍了模糊控制和PI控制系统。主要依据天线当前位置和速度采样反馈值,利用模糊控制原理对传统PI控制的比例、积分和微分参数进行在线整定,组成智能PI控制器,最后利用Matlab对控制系统进行仿真,得出仿真结果,并对仿真结果进行时域特性分析。

基于模糊平均电流控制的电池电源控制器研究

为保障控制器输出电压的稳定性,引进模拟控制理论,对电池电源控制器展开全面的设计研究。建立电池电源控制推挽式拓扑结构,划分电路工作过程;根据作业需求,设计内环和外环的控制器,内环控制器主要实现对系统内部细节的精确控制,而外环控制器用于调整内环的控制参数;参照PD控制器,开发模糊控制器,设计模糊推理规则,描述输入电压与输出电压之间的模糊关系,实现电压模糊化处理。仿真结果表明:提出的控制器在应用中的效果良好,此控制器可以实现对其运行中扰动的控制,以此种方式,保证电压的输出精度。