A Control Strategy for Terrain Adaptive Bipedal Locomotion

Rhythmic movements of a five-link sagittal biped with muscle-likeactuators are considered. In walking, as the support phases changecontact is periodically made with the environment. The inputs toevery actuator are modeled after the inputs to muscles in mammals. Thesystem possesses intrinsic position and velocity feedback due to theactuator dynamics. A control strategy is articulated that is novelin that it; a) is physiologically viable; b) simplifies the dynamics;and c) adapts to the speed of walking, going up and down stairs,going up or down inclines, maneuvering over obstacles or holes, andthe tempo and stride length of walking. Walking simulations of afive-link sagittal biped are presented.     

A Novel Method of Gait Synthesis for Bipedal Fast Locomotion

Common methods of gait generation of bipedal locomotion based on experimental results, can successfully synthesize biped joints’ profiles for a simple walking. However, most of these methods lack sufficient physical backgrounds which can cause major problems for bipeds when performing fast locomotion such as running and jumping. In order to develop a more accurate gait generation method, a thorough study of human running and jumping seems to be necessary. Most biomechanics researchers observed that human dynamics, during fast locomotion, can be modeled by a simple spring loaded inverted pendulum system. Considering this observation, a simple approach for bipedal gait generation in fast locomotion is introduced in this paper. This approach applies a nonlinear control method to synchronize the biped link-segmental dynamics with the spring-mass dynamics. This is done such that while the biped center of mass follows the trajectory of the mass-spring model, the whole biped performs the desired running/jumping process. A computer simulation is done on a three-link under-actuated biped model in order to obtain the robot joints’ profiles which ensure repeatable hopping. The initial results are found to be satisfactory, and improvements are currently underway to explore and enhance the capabilities of the proposed method.     

Simulating Adaptive Human Bipedal Locomotion Based on Phase Resetting Using Foot-Contact Information

Humans generate bipedal walking by cooperatively manipulating their complicated and redundant musculoskeletal systems to produce adaptive behaviors in diverse environments. To elucidate the mechanisms that generate adaptive human bipedal locomotion, we conduct numerical simulations based on a musculoskeletal model and a locomotor controller constructed from anatomical and physiological findings. In particular, we focus on the adaptive mechanism using phase resetting based on the foot-contact information that modulates the walking behavior. For that purpose, we first reconstruct walking behavior from the measured kinematic data. Next, we examine the roles of phase resetting on the generation of stable locomotion by disturbing the walking model. Our results indicate that phase resetting increases the robustness of the walking behavior against perturbations, suggesting that this mechanism contributes to the generation of adaptive human bipedal locomotion.     

Hybrid Invariant Manifolds in Systems With Impulse Effects With Application to Periodic Locomotion in Bipedal Robots

Motivated by the problem of controlling walking in a biped with series compliant actuation, this paper develops two main theorems relating to the stabilization of periodic orbits in systems with impulse effects. The first main result shows that when a periodic orbit of a system with impulse effects lies within a hybrid invariant manifold, there exist local coordinate transforms under which the Jacobian linearization of the Poincare return map has a block upper triangular structure. One diagonal block is the linearization of the system as restricted to the hybrid invariant manifold, also called the hybrid zero dynamics. The other is the product of two sensitivity matrices related to the transverse dynamics-one pertaining to the impact map and the other pertaining to the closed-loop vector field. When either of these sensitivity matrices is sufficiently close to zero, the stability of the return map is determined solely by the stability of the hybrid zero dynamics. The second main result of the paper details the construction of a hybrid invariant manifold, such as that required by the first main theorem. Forward invariance follows from the methods of Byrnes and Isidori, and impact invariance is achieved by a novel construction of impact-updated control parameters. In addition to providing impact invariance, the construction allows entries of the impact sensitivity matrix of the transverse dynamics to be made arbitrarily small. A simulation example is provided where stable walking is achieved in a 5-link biped with series compliant actuation.     

On the Passivity-Based Impedance Control of Flexible Joint Robots

In this paper, a novel type of impedance controllers for flexible joint robots is proposed. As a target impedance, a desired stiffness and damping are considered without inertia shaping. For this problem, two controllers of different complexity are proposed. Both have a cascaded structure with an inner torque feedback loop and an outer impedance controller. For the torque feedback, a physical interpretation as a scaling of the motor inertia is given, which allows to incorporate the torque feedback into a passivity-based analysis. The outer impedance control law is then designed differently for the two controllers. In the first approach, the stiffness and damping terms and the gravity compensation term are designed separately. This outer control loop uses only the motor position and velocity, but no noncollocated feedback of the joint torques or link side positions. In combination with the physical interpretation of torque feedback, this allows us to give a proof of the asymptotic stability of the closed-loop system based on the passivity properties of the system. The second control law is a refinement of this approach, in which the gravity compensation and the stiffness implementation are designed in a combined way. Thereby, a desired static stiffness relationship is obtained exactly. Additionally, some extensions of the controller to viscoelastic joints and to Cartesian impedance control are given. Finally, some experiments with the German Aerospace Center (DLR) lightweight robots verify the developed controllers and show the efficiency of the proposed control approach.     

有源箝位正激变换器无源控制方法的研究

以有源箝位正激变换器为研究对象,根据状态空间平均模型,建立系统误差模型,通过配置系统能量耗散特性方程中的无功力,保证系统的无源性,设计了一种无源化控制器。论文给出了变换器无源控制方法的推导过程和有源箝位正激变换器的无源控制策略;仿真和实验结果表明,该方案运行稳定,具有较强的鲁棒性、快速性和跟踪性,且纹波较小,控制算法简单等优点。     

基于无源性的永磁电机无速度传感器控制

针对永磁电机(PMSM)提出了一种无速度传感器的非线性控制策略. 该策略能在已知负载的基础上实现给定转矩的精确跟踪. 电机的速度通过一非线性降阶观测器来实现估计. 在此基础上, 利用电机的无源特性来设计电机的控制策略. 最后通过仿真验证了所提出策略的有效性.     

基于统一PCHD 建模的永磁同步电机无源控制

针对表面式永磁同步电机( SPMSM) 驱动系统的非线性特点,着眼于调速系统的 高性能要求,基于互联和阻尼配置的能量成形方法和端口受控耗散哈密顿( PCHD) 系统原理, 研究了SPMSM 系统的统一PCHD 建模和速度控制问题。首先,从能量平衡的观点,建立了逆 变器、考虑铁损的SPMSM、机械负载一体的不确定系统统一PCHD 数学模型,然后在此基础 上,设计了SPMSM 驱动系统的无源控制器,逆变器非线性扰动由扩张状态观测器进行补偿, 最后利用自抗扰控制设计了速度调节器得到q 轴期望的电流,所得控制器更加简单和容易实 现。仿真结果表明,所提方法实现了全局稳定性控制、鲁棒性强; 调速系统具有优良的动、静 态性能。     

无源控制下的动力电池多路均衡技术研究

针对当前动力电池均衡方案响应太慢、效率不高的问题,设计了一种基于反激变换器的多路均衡电路,该电路仅在常用双向均衡拓扑的基础上加上均衡电阻和旁路开关,即能实现多路能量转移.建立了带有源负载时的功率模块状态空间模型,根据非线性无源控制的相关理论,判定功率模块为线性无源,设计了无源控制器.引入无源控制后,均衡电流得到很好的控制,Matlab/Simulink仿真结果表明,无源控制下的多路均衡方案能进一步提高均衡响应速度,降低系统损耗.     

教学型双足步行机器人的结构及其控制电路设计

教学型双足机器人的研究制作是桌上型的重量很轻的作实验用的小型双足步行机器人。研究舵机的驱动控制方法、框架的设计以及制作能通过伺服电机控制运动的一种经济型的双足步行机器人。用单片机与CPLD控制伺服电机,通过预先给定机器人各个部位的运动轨迹,运算确定好各关节的旋转角度及控制系统的控制算法,以实现机器人的实际行走过程。     

微小气动机器人的移动控制

根据仿生尺蠖运动机理研制了一种用于人体腔道微创诊查的气动微机器人系统。该机器人系统由前支撑单元、后支撑单元和具有3个气室的橡胶驱动器三部分组成。设计了控制机器人移动的计算机电-气控制系统,通过控制该电-气系统的继电器和高速开关电磁阀来控制机器人系统的钳位气囊和驱动器气室内的气压。通过分析一个运动周期内机器人的运动状态,给出了机器人移动的控制算法,使机器人前、后支撑单元的气囊和驱动器的气室实现有规律的充气、保持及放气3种状态,从而实现有规律的运动。研究结果表明所设计的机器人具有仿生尺蠖移动机理的柔性结构,通过所设计的电-气控制系统可实现机器人的自动移动。     

基于脉宽差控制算法的双足竞步机器人设计

双足型机器人由于在工业应用和服务行业中有广泛的应用前景,因此具有非常重要的研究价值。本文设计了一个采用普通单片机构成的机器人控制方案,选用STC89C52型单片机作为机器人舵机控制板的主芯片,采用辉盛MG996通用型舵机作为机器人的关节驱动电机,使用Siemens公司的UG结构模型建模软件进行机器人结构零件设计,在实验室手工加工了全部机器人零件。     

Passivity-Based Robust Control Against Quantified False Data Injection Attacks in Cyber-Physical Systems

Secure control against cyber attacks becomes increasingly significant in cyber-physical systems (CPSs). False data injection attacks are a class of cyber attack...     

Style Invariant Locomotion Classification for Character Control

We present a real‐time system for character control that relies on the classification of locomotive actions in skeletal motion capture data. Our method is both progress dependent and style invariant. Two deep neural networks are used to correlate body shape and implicit dynamics to locomotive types and their respective progress. In comparison to related work, our approach does not require a setup step and enables the user to act in a natural, unconstrained manner. Also, our method displays better performance than the related work in scenarios where the actor performs sharp changes in direction and highly stylized motions while maintaining at least as good performance in other scenarios. Our motivation is to enable character control of non‐bipedal characters in virtual production and live immersive experiences, where mannerisms in the actor's performance may be an issue for previous methods.     

仿蚯蚓蠕动微机器人牵引与运动控制

为进入人体腔道开展作业,开发了一种直径6mm的仿蚯蚓多关节蠕动微机器人样机．机器人使用十字万向节连接直线驱动器,在弯曲腔道中能自适应改变自身姿态．基于Preisach模型和偏转模型,提出了形状记忆合金偏转机构的前馈控制方案,头舱控制最大偏转误差为2.6°．基于新型蠕动原理,建立了牵引模型,给出了有效驱动的条件．对机器人的牵引力、运动速度、在不同摩擦系数介质表面上的运动能力、头舱姿态进行了试验．结果表明,机器人的爬坡能力依赖于机器人和运动表面间的摩擦系数,新型蠕动原理能提供较大的牵引力,合适的驱动频率下可以得到最大的运动速度．     

动态双足机器人的控制与优化研究进展

对动态双足机器人的可控周期步态的稳定性、鲁棒性和优化控制策略的国内外研究现状与发展趋势进行了探讨.首先,介绍动态双足机器人的动力学数学模型,进一步,提出动态双足机器人运动步态和控制系统原理;其次,讨论动态双足机器人可控周期步态稳定性现有的研究方法,分析这些方法中存在的缺点与不足;再次,研究动态双足机器人的可控周期步态优化控制策略,阐明各种策略的优缺点;最后,给出动态双足机器人研究领域的难点问题和未来工作,展望动态双足机器人可控周期步态与鲁棒稳定性及其应用的研究思路.     

面向变高度连续台阶的双足欠驱动步行稳定控制

针对欠驱动双足机器人在已知变高度台阶上的稳定控制,提出了一种基于自适应前馈算法的稳定步行控制策略．首先,考虑地面变形,将地面等效为“弹簧-阻尼”系统,并建立“机器人-台阶”耦合动力学模型．其次,将“机器人-台阶”这一“多输入-多输出”模型简化为由质心位移和速度构成的“单输入-单输出”模型．然后,使用变坡度斜坡等效变高度台阶,根据台阶高度确定等效斜坡倾角和机器人理想步长;同时引入自适应控制系数,并根据等效斜坡倾角调整该控制系数,实现质心对参考速度的跟踪．最后,在台阶高度变化小于0.032 m的环境中进行数值仿真试验,验证控制策略的有效性．仿真结果表明：本文提出的控制策略可以实现已知变高度台阶上的稳定步行．     

基于失衡度的双足机器人控制方法研究

为了解决双足机器人在强干扰下易失去平衡而摔倒的问题,提出一种基于失衡度的欠驱动双足机器人的稳定控制方法。该方法分析了多种情况下欠驱动双足机器人单脚支撑期动力学模型,用线性倒立摆模型模拟机器人的失衡度,并根据机器人受到的外部干扰的强度变化,将失衡度分为三个级别,在不同的失衡度级别内,采用相应的动力学模型及跟踪、姿态、步态切换控制方法。仿真结果表明,该方法具有较高的稳定性、实用性,可以实时控制欠驱动双足机器人步态。     

仿生六足爬行机器人运动控制技术研究

在对生物神经系统结构与功能进行分析和借鉴的基础上,采用模块化分散递阶控制技术对仿生六足爬行机器人进行实时控制,解决了仿生六足机器人实时精确运动控制的问题,并在机器人关节控制模块中运用了模糊小波神经网络控制,实现了机器人肢体运动的快速精确跟踪;通过Matlab进行的轨迹跟踪仿真试验证实：机器人步行足的运动轨迹与期望曲线基本吻合,具有较好的跟踪特性,且误差曲线快速收敛,静态误差趋近于零;由此表明,该机器人控制系统可靠性高,实时性强,具有较好的动、静态特性,以及良好的抗干扰能力和自适应能力,克服了传统控制方法存在的控制模型难以建立、对环境适应能力差等缺点,为仿生六足爬行机器人的进一步研究奠定了坚实的基础。