Dynamical analysis and performance evaluation of a biped robot under multi-source random disturbances

During bipedal walking,it is critical to detect and adjust the robot postures by feedback control to maintain its normal state amidst multi-source random disturbances arising from some unavoidable uncertain factors.The radical basis function（RBF）neural network model of a five-link biped robot is established,and two certain disturbances and a randomly uncertain disturbance are then mixed with the optimal torques in the network model to study the performance of the biped robot by several evaluation indices and a specific Poincar′e map.In contrast with the simulations,the response varies as desired under optimal inputting while the output is fluctuating in the situation of disturbance driving.Simulation results from noise inputting also show that the dynamics of the robot is less sensitive to the disturbance of knee joint input of the swing leg than those of the other three joints,the response errors of the biped will be increasing with higher disturbance levels,and especially there are larger output fluctuations in the knee and hip joints of the swing leg.

A kind of noise-induced transition to noisy chaos in stochastically perturbed dynamical system

We investigate a kind of noise-induced transition to noisy chaos in dynamical systems. Due to similar phenomenological structures of stable hyperbolic attractors excited by various physical realizations from a given stationary random process, a specific Poincar6 map is established for stochastically perturbed quasi-Hamiltonian system. Based on this kind of map, various point sets in the Poincar6＇s cross-section and dynamical transitions can be analyzed. Results from the customary Duffing oscillator show that, the point sets in the Poincare＇s global cross-section will be highly compressed in one direction, and extend slowly along the deterministic period-doubling bifurcation trail in another direction when the strength of the harmonic excitation is fixed while the strength of the stochastic excitation is slowly increased. This kind of transition is called the noise-induced point-overspreading route to noisy chaos.

A new procedure for exploring chaotic attractors in nonlinear dynamical systems under random excitations

Due to uncertain push-pull action across boundaries between different attractive domains by random excitations, attractors of a dynamical system will drift in the phase space, which readily leads to colliding and mixing with each other, so it is very difficult to identify irregular signals evolving from arbitrary initial states. Here, periodic attractors from the simple cell mapping method are further iterated by a specific Poincare map in order to observe more elaborate structures and drifts as well as possible dynamical bifurcations. The panorama of a chaotic attractor can also be displayed to a great extent by this newly developed procedure. From the positions and the variations of attractors in the phase space, the action mechanism of bounded noise excitation is studied in detail. Several numerical examples are employed to illustrate the present procedure. It is seen that the dynamical identification and the bifurcation analysis can be effectively performed by this procedure.

Input torque sensitivity to uncertain parameters in biped robot

Input torque is the main power to maintain bipedal walking of robot, and can be calculated from trajectory planning and dynamic modeling on biped robot. During bipedal walking, the input torque is usually required to be adjusted due to some uncertain parameters arising from objective or subjective factors in the dynamical model to maintain the pre-planned stable trajectory. Here, a planar 5-link biped robot is used as an illustrating example to investigate the effects of uncertain parameters on the input torques. Kine-matic equations of the biped robot are firstly established by the third-order spline curves based on the trajectory planning method, and the dynamic modeling is accomplished by taking both the certain and uncertain parameters into account. Next, several evaluation indices on input torques are intro-duced to perform sensitivity analysis of the input torque with respect to the uncertain parameters. Finally, based on the Monte Carlo simulation, the values of evaluation indices on input torques are presented, from which all the robot param-eters are classified into three categories, i.e., strongly sensi-tive, sensitive and almost insensitive parameters.

双跨转子的随机不确定性非参数建模与可靠性分析（英文）

目的:旋转机械由于工作环境复杂,在运行过程中会不可避免地受到各种不确定性因素的影响,从而引发转子系统的异常振动。因此,迫切需要对系统工作状态开展可靠性分析。本文将外部扰动不确定性与模型不确定性考虑在内,旨在建立转子系统运行状态的可靠性评估指标,丰富转子动力学理论体系,为工程应用提供参考。创新点:1.采用非参数法进行建模,能够将外部扰动不确定性与模型不确定性同时包含在内;2.在非参数建模基础上,结合响应谱分析法进行可靠性计算,可避免对系统先验知识的需求并降低计算过程的复杂性;3.将短周期预测理论扩展应用于可靠性分析验证。方法:1.借助非参数法建立转子系统的随机不确定性模型;2.结合响应谱分析法推导出系统可靠性指标计算式;3.采用短周期预测方法对模拟数据统计指标进行计算与验证。结论:1.本方法可用于评估大型复杂旋转机械系统的可靠性,尤其对于服役时间较长导致系统参数出现不确定性变化的情形;2.本研究结果可为大型复杂旋转机械的设计、运行和控制提供理论基础,同时也可以为其他类型机械设备的可靠性分析和预测方法提供参考。

Control strategy for gait transition of an underactuated 3D bipedal robot

Significant research interest has recently been attracted to the study of bipedal robots due to the wide variety of their potential applications.In reality,bipedal robots are often required to perform gait transitions to achieve flexible walking.In this paper,we consider the gait transition of a five-link underactuated three-dimensional(3 D)bipedal robot,and propose a two-layer control strategy.The strategy consists of a unique,event-based,feedback controller whose feedback gain in each step is updated by an adaptive control law,and a transition controller that guides the robot from the current gait to a neighboring point of the target gait so that the state trajectory can smoothly converge to the target gait.Compared with previous works,the transition controller is parameterized and its control parameters are obtained by solving an optimization problem to guarantee the physical constraints in the transition process.Finally,the effectiveness of the control strategy is illustrated on the underactuated 3 D bipedal robot.