Design of a cyclic inhibitory CPG controller for the locomotion of a snakelike robot

The rhythmic locomotion of a creature is a self-excitation behavior of the CPG (central pattern generator), which makes it supremely adapted for environment. Based on this fact, firstly, a snake-like robot controller with cyclic inhibitory CPG model was designed, and then the stability of a single neuron, CPG model and the NON (neuron oscillator network) was analyzed. By implementing this control architecture to a simulator based on the mechanical dynamics of a real snake-like robot named Perambulator-I, we presented preliminary rules for parameter setting of the CPG controller to modulate the number of S shapes, the curve of the body shape, locomotion velocity, and the curve of the locomotion trajectory for serpentine locomotion. Moreover, we demonstrated that Perambulator-I can successfully exhibit serpentine locomotion by using the output of the proposed CPG controller. The results of this paper provide a realistic approach for designing an artificial CPG controller. __________ Translated from Chinese Journal of Mechanical Engineering, 2006, 42(5) (in Chinese)     

一种双足机器人变结构控制的ZMP补偿优化方法

针对双足机器人系统,设计了一种变结构轨迹跟踪控制器。基于双足机器人系统ZMP(zero moment point)方程和实际ZMP信息,提出一种ZMP补偿优化方法,通过在线实时调整机器人躯体重心竖直方向上的位置来补偿回复稳定姿态所必需的力矩,最终产生修正的ZMP轨迹。12自由度的双足机器人动力学仿真验证了所提出优化方法的鲁棒性和适用性,而且机器人能在一定范围外力的干扰下回复稳定姿态步行。     

基于中枢神经模式的四足机器人步态控制

为实现四足机器人稳定的节律性行走,研究基于中枢神经模式发生器(Central pattern generator,CPG)的比例步态控制方式。构建互抑神经元组成的振荡器模型,并基于振荡器模型组建四足机器人髋关节CPG网络。通过仿真研究得到模型各参数与CPG网络输出特性之间的关系,确定一套整定后CPG网络的模型参数,提出四足机器人比例步态,通过CPG模型阈值的调整可实现不同占空比的步态。对基于CPG网络的步态反射特性进行分析。试验表明,该方法可实现稳定的四足机器人行走,且具备一定的障碍物反射能力,具有较好的环境适应性。     

非线性振子的CPG步态控制方法研究

通过分析生物节律运动机理．提出基于中枢模式发生器模型的步态控制方法。利用改进的Vanderpol方程构造非线性振子作为单个CPG的数学模型。采用KB法得到振荡神经元一阶近似周期解,在此基础上设计具有线性反馈项的环状CPG网络模型,并给出了控制机器人步态协调运动方法。仿真结果验证了基于CPG模型的控制方法可以有效生成节律运动的常规步态并实现步态切换。     

Energy dissipation rate control and parallel equations solving method for planar spined quadruped bouncing robot

This paper continues our investigation into Energy dissipation rate control (EDRC) and Parallel equations solving method (PESM). Our previous works showed how EDRC enables us to provide stable walking or running gaits for legged robots via controlling robot’s loss of energy rate during Impact phases (IP). This is while PESM facilitates the trajectory designing process of the robot’s active joints during each Single support phase (SSP) by solving the robot’s inverse kinematic and inverse dynamic equations in parallel. Even though PESM is very powerful and suitable for both quadruped robot, and despite the under actuation problem at the ankle joint, and biped robots, despite the presence of Zero momentum point criteria (ZMP) at the ankle joint, still, this method is limited to robots just with three and five DoFs. Therefore, the main purpose hereis to show how it is possible to extend the application of PESL to a spined quadruped robot with four DoFs by employment of the Central pattern generator (CPG) controller units and finding a connection among CPG’s output, PESM and the robot’s foot placement. Besides, as EDRC is employed to realize a stable bouncing gait for the robot, a whole numerical study is performed on the robot’s impact dynamic equations to evaluate the effect of spine joint on the robot’s impact dynamics.

     

中枢模式发生器与足端轨迹的非线性映射

控制的仿生性和行走的稳定性是四足机器人步态研究中重要的两个方面。 为了提高四足机器人运动的稳定性,本文通 过 Hopf 振荡器搭建了 CPG 模型,分别实现了多种步态及步态之间的转换。 比较了基于 CPG 的步态控制方法和轨迹规划的步 态规划方法在行走上的优劣性。 为了同时利用 CPG 控制和轨迹规划的优点,提出采用神经网络将 CPG 控制曲线与足端轨迹 逆运动学获得的驱动曲线进行非线性映射,使得四足机器人在控制上具备仿生特性,在足端接触上具备零冲击特性。 仿真和实 验结果表明,采用 CPG 的步态生成方法和轨迹规划方法四足机器人的行走速度理论行走速度 80 mm/ s 相近,但采用 CPG 的步 态生成方法四足机器人侧向位移在±10 mm 以内且俯仰角在±1. 5°之间,而采用轨迹规划的控制方法四足机器人侧向位移在 ±35 mm 以内且俯仰角在±4°之间,可见两种控制方式对侧向偏移和俯仰运动的表现不一致。 通过实验测量可知,机器人采用 walk 步态行走速度为 18. 57 mm/ s,与理论行走速度 20 mm/ s 接近,步态转换后以 trot 步态行走,行走速度为 76. 15 mm/ s,与理 论行走速度 80 mm/ s 接近,少许误差可能是装配和行走过程打滑导致的。 测量其侧向偏移程度可知,其侧向的偏移量左侧在 15 mm 内,右侧在 25 mm 内,其侧向偏移量均在合适的范围内,证明所提算法的有效性。     

类人机器人复杂运动的状态转换规划方法研究

提出一种针对类人机器人复杂运动的状态转换规划方法。该方法采用状态空间描述机器人的动作序列，以ZMP稳定判据对运动中的状态节点进行稳定性分析，采用多项式插值的方法实现状态之间的转换，对不满足稳定性要求的插值轨迹采取增加状态节点重新修正的方法，从而完成类人机器人的运动规划。机器人的起立过程的仿真结果表明，该方法简单可行、有效。     

基于模糊神经网络的不确定机器人实时轨迹跟踪控制的研究

针对机器人建模的不精确性以及扰动的存在给机器人控制增加难度的问题,提出了一种基于模糊神经网络的不确定机器人实时轨迹跟踪控制方法。该控制方法的控制器由模糊神经网络(FNN)控制器和CMAC控制器组成,FNN控制器代替传统的计算力矩法,CMAC控制器在线补偿控制误差,有效补偿机器人存在的各种不确定性。对二自由度机器人的仿真结果表明了所提出的控制方法的可行性。     

Real-Time Simulator based hybrid control of DFIG-WES

This paper presents the analysis and design of recurrent neural network (RNN) and proportional and integral(PI) controller based hybrid control(HC) of doubly fed induction generator (DFIG). The proposed HC shows the quick dynamic and good transient response during the sudden changes in wind speed as well as generator speed. Further performance of proposed hybrid controller has been analyzed independently with RNN and PI control as its components. The HC along with RNN gives effective performance compared to conventional DTC (CDTC) and PI DTC in terms of flux ripples,torque ripples and settling time. The proposed technique is implemented in real-time simulator (RTS) based OPAL-RT and MATLAB/SIMULINK environment at a rating of 5.5 KW system under steeply and randomly change in wind velocity.     

Hybrid DSO-GA-based sensorless optimal control strategy for wind turbine generators

The operation of a wind turbine generator involves natural uncertainty due to aerodynamic characteristics, resulting in a system that performs inefficiently. In general, the conventional controller now in wide use is not suitable for every operating point, because its tuning parameters and set-points do not meet the varying system characteristics. A study into an optimal control technique is conducted to reduce the negative effects of inherent uncertainty in system operation. In order to resolve the uncertainty problem, an optimal control method for an effective wind turbine generator is designed on the basis of a sensorless frame by utilizing a hybrid of the direct search optimization method (DSO) and the genetic algorithm (GA). This method is easy to implement and computation of functional derivatives is not necessary. The conventional GA is well known for its high performance in global optimization and its effectiveness in making ideal choices for control variables. The proposed DSO-GA hybrid differs from the conventional GA in terms of the sampling survey and the crossover operation. Moreover, the proposed multivariable optimal control strategy is a sensorless optimization technique that determines the pitch angle of the blades and the yaw angle of the nacelles to produce stable maximum power from a wind turbine system under steady-state operation. The proposed DSO-GA controller is implemented for a lab-scale wind turbine generator exposed to artificial wind, and the experimental results constitute a 3-D performance surface model of output voltage, which is used as an objective function for simulation. The optimization procedure with the objective function is carried out by means of the conventional and proposed methods, whose results reveal that the proposed DSO-GA optimizer yields far better performance in terms of generation number, convergence rate, and robustness. Both techniques are applied to a wind power generator through simulation and experiments. The performances are compared, and conclusions are drawn for each case.     

直线电机精密定位平台轨迹跟踪控制器设计

为了实现直线电机精密定位平台的位置和速度的轨迹跟踪控制,本文基于内模控制（IMC）的基本原理,在直线电机精密定位平台参数辨识的基础上,设计了定位平台速度环的模型状态反馈（MSF）控制器和基于位置环PID和速度环MSF的级联控制器。将PID/MSF级联控制器与速度/加速度前馈控制（VFC/AFC）相结合,构成了PID/MSF+VFC/AFC的复合轨迹跟踪控制器。该复合轨迹跟踪控制器通过整定速度前馈的增益来改善位置环偏差控制的跟踪滞后现象和动态响应,增加控制系统的稳定性和伺服精度;通过整定加速度前馈的增益在不减小级联控制器位置环增益的前提下,减小速度前馈带来的超调量,提高轨迹跟踪精度。基于MATLAB/dSPACE实时仿真控制平台,实现了某直线电机平台的轨迹跟踪控制。仿真和实验结果表明,该轨迹跟踪控制器的轨迹跟踪精度为±0.028 mm,定位精度为±4 μm,满足直线电机精密定位平台轨迹跟踪控制的要求。     

滑模变结构控制方法在混合输入平面五杆机构中的应用和稳定性分析

混合输入平面五杆机构具有两个自由度,其动力学模型是一个高度非线性和强耦合系统。基于李亚普诺夫函数、利用滑模变结构控制理论(slid ing mode control)设计了控制器,并对系统进行了控制仿真。仿真结果表明,在不改变机构结构和进行质量重布的情况下,就可以实现较高精度的轨迹跟踪。理论分析证明,所设计的滑模变结构控制器是全局稳定的。     

采用内模控制理论的双馈感应风机鲁棒控制器设计

针对工程中双馈感应电机转子电流控制器参数整定的问题,提出一种利用内模控制理论设计转子电流控制器的鲁棒控制方法。首先定义内模控制的灵敏度函数和互补灵敏度函数,并推导双馈感应电机转子电流控制系统传递函数,建立了转子电流内环的内模数学模型。IMC控制器的设计以平方积分误差值和鲁棒稳定M值为准则,并与传统比例积分控制器进行比较。通过对1.5 MW双馈感应电机的MATLAB/SIMULINK仿真表明,本文方法稳态跟踪精度高、动态响应快、对模型误差和外界干扰具有较好的鲁棒性。最后在11 k W的双馈风机实验平台上验证了所提方法的有效性。     

混合输入机构的模糊自适应变结构控制

针对混合输入机构中常速电机可不可控的特点,提出了基于常速电机位置跟踪的控制策略来对伺服电机进行控制,对常速电机的速度波动进行补偿,并给出了控制框图。因为系统的精确动力学模型难以获得,故考虑系统参数的不确定、外部扰动和非线性摩擦,设计了模糊自适应滑模变结构控制器以实现混合输入机构的轨迹跟踪。应用模糊自适应推理逼近系统的不确定之和,从而得到连续的控制增益,消除了变结构控制的抖振。     

双足机器人CPG控制研究

根据动物运动机制,提出了基于中枢模式发生器（central pattern generator,CPG）的双足机器人运动控制方法;采用Kimura神经元振荡器模型设计了双足机器人的CPG控制网络架构,分别用于控制双足机器人的髋关节、膝关节和踝关节。通过Matlab仿真和实体实验,验证了所设计的机器人CPG网络架构及双足机器人CPG控制方法的可行性和有效性。     

Simultaneous trajectory tracking control of position and force with pneumatic cylinder driving apparatus

In this study, a position and force simultaneous trajectory tracking control algorithm is proposed for a driving apparatus that consists of two pneumatic cylinders connected in series. The controller applied to the driving apparatus is composed of a non-interaction controller to compensate for interaction between cylinders and a disturbance observer aimed to reduce the effect of model discrepancy that cannot be compensated by the non-interaction controller. The effectiveness of the proposed control algorithm is proved by experimental results.     

Energy efficient walking control for biped robots using interval type-2 fuzzy logic systems and optimized iteration algorithm

An energy efficient approach is proposed for the walking control of bipedal robots. To compensate the ZMP error caused by model uncertainties and external disturbances, we design a new walking controller in this paper. Different from currently available control schemes for cancelling ZMP error, our newly proposed one additionally incorporates a fuzzy logic systems(FLSs) mechanism and an iterative mechanism. By employing FLSs to deduce Center of Mass(CoM) correction according to ZMP error and designing iterative mechanism to compute the optimal joint position, the newly proposed controller exhibits an excellent performance. To tackle the control difficulties arising from physical constraints of actuators and hard-to-stabilization of biped robot, an optimized control algorithm is included in the iterative mechanism to guarantee the convergence to the optimal solution. Moreover, the interval type-2 FLSs are adopted to handle the uncertainties. Finally, the experiment results are provided to validate the proposed control scheme.     

串联式混合动力发电机励磁控制器硬件设计

发电机励磁控制器在串联混合动力系统中是非常重要的一个环节,本文在天津市科委的支持下,对西安电机厂的Z4-180-11发电机进行了控制器的匹配设计并有针对性地作了调试试验,验证了该控制器有效。该套励磁控制器的调试成功为下一步工作打下了良好的基础。     

基于DSP的机械臂约束预测控制系统设计

针对机械臂的实时控制问题,基于约束预测控制,提出了一种机械臂实时运动控制方法。介绍了机械臂动力学模型并进行了线性化处理,以降低算法复杂度、保证实时性。设计了轨迹跟踪控制器和约束预测控制器,其中轨迹跟踪控制器采用最优反馈控制律,可确保机械臂按参考轨迹运动;而约束预测控制器则在考虑机械臂物理约束的情况下,为跟踪控制器提供最优参考轨迹。以DSP作为核心控制器,搭建了机械臂控制系统,同时给出了硬件和软件设计方法。以梯形和三次多项式轨迹为例,进行了系统功能测试,测试结果表明了所述控制系统的可行性和有效性。     

即时学习型迭代学习控制在励磁控制中的应用

将即时学习算法型迭代学习控制引入发电机的励磁控制。运用即时学习算法来解决系统的迭代学习控制初值问题,有效地估计初始控制量,加快了算法的收敛速度。仿真结果表明,所设计的励磁控制器与常规PID控制器和非即时学习型励磁控制器相比其收敛速度明显加快,具有更强的维持机端电压的能力。