基于Actor-Critic和神经网络的闭环脑机接口控制器设计

在皮层神经元放电活动模型的基础上进行单关节自发运动的研究,从控制理论的角度分析闭环脑机接口的工作原理.使用卡尔曼滤波器和人工神经网络设计系统的解码器替代原系统的脊髓电流,并且比较这两种解码器的优劣.由于在无感知反馈的信号下,解码器的性能下降得比较明显,使用强化学习中Actor-Critic算法结合人工神经网络设计PID控制器,用以产生刺激信号来刺激大脑皮层神经元,使其能够跟踪有感知反馈信号时皮层神经元的放电活动,从而恢复解码器的性能.最后,通过与其他控制算法对比,验证了基于强化学习算法的人工感知反馈信号设计的有效性.     

基于脑机接口与双激光雷达的移动车导航系统

针对脑机接口信噪比低、准确率差和延时长等问题,提出了基于机器智能辅助的室外移动机器人脑机接口导航方法.设计并实现了一个基于脑机接口与双激光雷达的移动车导航系统.该系统首先采用了基于双激光雷达的改进的角度势场法进行局部路径规划,然后结合脑机接口系统获取的导航意图,经过融合决策给出控制命令,驱动一辆经过机械系统改装的电动汽车.实验表明,该系统能根据环境障碍信息和脑机控制意图实现智能避障与人机协同导航,具有更高的准确性、容错性和鲁棒性.     

基于辅助变量的闭环系统子空间辨识

提出一种基于辅助变量的子空间辨识方法,适用于控制器信息未知以及参考输入已知的闭环系统参数辨识.通过将输入-输出数据块正交投影到辅助变量的行空间,直接得到扩展观测矩阵垂空间的估计.由此可从闭环系统中提取出对象模型信息,同时由SVD分解得到扩展观测矩阵与下三角Toeplitz矩阵的估计.给出了系统参数矩阵、噪声矩阵的计算方法.将所提出的子空间辨识方法应用于闭环动态的系统参数估计,其结果表明了该方法的有效性.     

模型预测控制方法在抑制Ⅱ型飞行员诱发振荡上的应用

当速率限制器饱和时,其输出相对输入会产生相位滞后和幅值降低.基于模型预测控制(MPC)方法设计了控制器,将速率限制条件转化为系统输入的约束条件,从而最大限度地克服由速率限制器饱和引发的Ⅱ型飞行员诱发振荡(PIOs).分析了在正弦输入信号作用下控制器对系统相位的影响,并将控制器应用于人—机闭环系统进行仿真.结果表明,MPC控制器可使输出相位超前,PIOs未发生时可辅助飞行员消除系统误差,振荡条件下可完全克服速率限制器的影响,有效抑制PIOs发生.     

基于模型的闭环系统故障检测的一种新方法

针对在闭环控制系统中,如何取得产生残差的最佳信号的问题,通过对单输入单输出闭环系统各种故障的Matlab仿真研究及结果分析,提出了一种基于模型的闭环系统故障检测的新方法。该方法把控制器的输出残差和系统的输出残差结合起来检测故障,并且考虑到了在实际系统中控制器可能饱和的实际情况。这种检测故障的新方法对于实际系统可能发生的各种故障(如执行器,传感器故障)更为有效,可以提高系统检测故障的性能,减少了系统故障的漏报率。     

参数空间中鲁棒稳定性问题

本文研究了单输入多输出(SIMO)和多输入单输出(MISO)线性定常控制系统在对象 参数扰动下的鲁棒稳定性问题,并对一给定的控制器,系统在标称参数P°下闭环渐稳的情 况,提出了在参数空间中构造比中心位于P°的最大稳定超球还要大的稳定超球的方法,从而 改善了鲁棒稳定性判据.     

基于mu节律能量的运动意识分类研究

基于脑电(EEG)的脑机接口(BCI)是在人脑和计算机或其它电子设备之间建立不依赖于常规大脑信息输出通路(外周神经和肌肉组织)的全新对外信息交流和控制技术。文中提出了基于mu节律能量为脑电特征的意识任务分类思想,对被测试者想象左右手运动的脑电mu节律能量(二阶矩)及其动态变化情况进行研究。实验结果表明,基于mu节律能量的想象左右手运动意识识别和分类的正确识别率可达85%。二阶矩计算简单,而且可在线计算,故可以认为,基于mu节律能量为脑电特征的意识任务分类在脑机接口的应用中有较高的实用价值。     

感知器算法在运动想象脑电模式识别中的应用

基于脑电(EEG)的脑机接口(BCI)是在人脑和计算机或其它电子设备之间建立不依赖于常规大脑信息输出通路(外周神经和肌肉组织)的全新对外信息交流和控制技术。及时有效地提取和识别与运动想象相关的脑电模式可以帮助严重瘫痪病人控制光标或辅助运动设备以替代其受损的运动功能,建立一种与外界交流沟通的新途径。论文将以EEG(C3,C4)两个通道的mu节律能量作为特征向量,用感知器算法对左右手运动想象脑电模式进行识别,实验结果表明,正确识别率可达87.86%。由于感知器算法计算简单,故可以认为,感知器算法在脑机接口的应用中有较高的实用价值。     

浅谈脑-机接口技术

脑机接口是近年来发展起来的一种人机接口,它不依赖于大脑的正常输出通路(即外围神经和肌肉组织),就可以实现人脑与外界(计算机或其它外部装置)直接通信的系统。本文概述了基于脑信号的脑机接口的基本结构,常用算法及应用前景。     

带传输滞后的离散系统的观测器及输出动态反馈

针对带输出传输滞后的线性离散系统,讨论了其状态观测器设计问题.利用滞后输出信息,给出了状态观测器的设计方法,并得到状态观测器存在的充要条件,进而设计出基于观测器的输出动态反馈控制器,证明了闭环系统满足极点分离原理.数值仿真验证了所提出方法的有效性.     

深海自持式智能浮标双闭环模糊PID定深控制

针对深海自持式智能浮标运动模型非线性、强耦合性的特点,提出了一种基于双闭环反馈回路的模糊比例-积分-微分（proportion-integral-derivative,PID）定深控制器.根据浮标的浮力调节机构,分析了浮标的运动过程,建立了非线性运动方程.针对外环深度反馈回路,设计了模糊控制器.基于内环速度反馈回路与模糊控制器,设计了联级模糊PID定深控制器.传统PID定深控制器超调量5.6%,最终在目标深度±30 m范围内震荡,而双闭环模糊PID定深控制器在相同的上升时间内,超调量2.0%,深度误差控制在1.0%以内.存在外界扰动的情况下,通过双闭环模糊PID定深控制器的调节,浮标仍可以稳定在目标深度内.仿真结果表明,所建立的双闭环模糊PID定深控制系统具有良好的控制效果和稳定性.     

Simple control method for integrating processes with long deadtime

Control of integrating processes with long deadtime is a challenging problem. Using original Smith predictor control structure will result in an offset problem during load disturbance. Using the internal model control (IMC) principle to design the control structure will result in large overshoot during servo response. In this work, a simple modified Smith predictor controller design is proposed for this important type of system. The overall control structure has only two physically meaningful tuning parameters. One is used to set the speed of the closed-loop servo response and the other tuning parameter is used to set the speed of the closed-loop load response. Two examples are used to demonstrate the improved closed-loop performance of the proposed controller design.     

基于内模控制的改进型三相PWM整流器

针对三相电压型PWM整流器的双闭环控制系统直流母线电压超调较大、对扰动克服能力不强、鲁棒性差等问题,本文对控制系统进行了改进,在电压外环设计一种基于内模原理的控制器以取代传统PI控制器,并对内模控制器中滤波器部分的参数设计进行分析,最后使用MATLAB/SIMULINK进行仿真研究,并与电压外环采用PI控制器的系统性能进行比较。仿真结果表明,在电压环采用内模控制器,可以有效降低直流母线电压超调,快速抑制扰动,具有良好的鲁棒性,性能优于传统PI调节器。     

An improved state-space model structure and a corresponding predictive functional control design with improved control performance

Conventional state-space model predictive control requires a state estimator/observer to access the state information for feedback controller design. Its drawbacks are the numerical convergence stability of the observer and closed-loop control performance deterioration with activated plant input/output constraints. The recent direct use of measured input and output variables to formulate a non-minimal state-space (NMSS) model overcomes these problems, but the subsequent controller is too sensitive to model mismatch. In this article, an improved structure of NMSS model that incorporates the output-tracking error is first formulated and then a subsequent predictive functional control design is proposed. The proposed controller is tested on both model match and model mismatch cases for comparison with previous controllers. Results show that control performance is improved. In addition, a linear programming method for constraints dealing and a closed form of transfer function representation of the control system are provided for further insight into the proposed method.     

基于PID和LQR的四旋翼无人机控制系统研究

为提高四旋翼无人机的飞行稳定性、无人飞行器控制系统的鲁棒性和控制精度,以建立的四旋翼无人机飞行控制系统模型为基础,采用现代控制理论与传统控制论相结合的方法,针对姿态角速率、姿态角分别设计内环LQR(线性二次型调节器)控制器,及外环PID控制的双回路闲环控制器.充分利用PID控制器易于掌握且对模型要求精度低、LQR控制器能改善内回路的动态特性和稳态性能的特点,完成四旋翼无人机的飞行控制.通过实验遴选该双闭环控制器相关参数并进行优化,实验结果表明所设计的双回路控制器控制性能指标良好.     

Composite nonlinear feedback design for discrete-time switching systems with disturbances and input saturation

This paper addresses the problem of robust controller design for a class of discrete-time switching systems with input saturation. To this aim, the composite nonlinear feedback method is extended to design a robust controller with improved performances in terms of the response speed and overshoot in the presence of disturbances and input saturation. The proposed approach is theoretically analysed and its closed-loop stability is proved. Then, the performance of the proposed method is verified using numerical simulations.     

Vibration control of the flexible manipulator with input constraints and external disturbances based on Nussbaum function

In this paper, a boundary control scheme based on the partial differential equation (PDE) model is proposed for the vibration control problem of the flexible manipulator with input constraints and external disturbances. Based on the backstepping method, two boundary controllers are designed to stabilize the position loop subsystem and the attitude loop subsystem, respectively, and auxiliary systems based on the smooth hyperbolic tangent function and Nussbaum function are designed in the controllers to deal with the input saturation and external disturbances. The Nussbaum function can overcome the difficulties in controller design and stability analysis caused by the derivatives of smooth hyperbolic tangent functions. The well-posedness of the closed-loop system is proven by employing the semigroup theory, and the uniformly bounded stability is proved by Lyapunov direct method. Finally, the performance of the proposed control laws is verified by numerical simulations.     

Optimal probability density function control for NARMAX stochastic systems

This paper presents a new control strategy for a class of non-Gaussian stochastic systems so that the output probability density function (PDF) of the system can be made to follow a desired PDF. The system considered is represented by an Nonlinear AutoRegressive and Moving Average with eXogenous (NARMAX) inputs with input channel time-delay and non-Gaussian noise. A multi-step-ahead nonlinear cumulative cost function is used to improve tracking performance. For this purpose, a relationship between the PDFs of all the inputs and the PDFs of multiple-step-ahead output is formulated by constructing an auxiliary multivariate mapping. By minimizing this performance function, a new explicit predictive controller design algorithm is established with less conservatism than some previous results. Furthermore, an improved approach is developed to guarantee the local stability of the closed-loop system by tuning the weighting parameters recursively. Simulations are given to demonstrate the effectiveness of the proposed control algorithm and desired results have been obtained.     

Design of decentralized controllers for MIMO processes

In this paper, the design of decentralized PID controller for interactive and delay time processes is proposed. Direct controller synthesis approach is used to obtain parameters of the multi-loop controllers. A detuning factor for each loop is specified based on the closed-loop time constant. Then appropriate controller settings are determined using the Maclaurin series expansion and the model of the process. The success of the proposed algorithm is based on the detuning parameter thus the selection of the desired closed-loop time constant is an important factor. The proposed method has no limitations regarding systems weak or strong interactions, multiple delays, and its operating behaviors such as monotonic or oscillatory. The proposed algorithm is simpler and improved performance of various processes are achieved as compared to some of the prevalent techniques. Simulation examples demonstrate the usefulness of the proposed method.