Exploring human rhythmic gait movement in the role of cerebral cortex signal

The rhythmic movement is a spontaneous behavior due to the central pattern generator (CPG). At present, the CPG model only shows the spontaneous behavior, but does not refer to the instruction regulation role of the cerebral cortex. In this paper, a modified model based on the Matsuoka neural oscillator theory is presented to better show the regulation role of the cerebral cortex signal to the CPG neuronal network. The complex interaction between the input signal and other parameters in the CPG network is established, making all parameters of the CPG vary with the input signal. In this way, the effect of the input signal to the CPG network is enhanced so that the CPG network can express the self-regulation movement state instead of being limited to the spontaneous behavior, and thus the regulation role of the cerebral cortex signal can be reflected. Numerical simulation shows that the modified model can generate various movement forms with different modes, frequencies, and interchanges between them. It is revealed in theories that the cerebral cortex signal can regulate the mode and frequency of the gait in the course of the gait movement.     

Exploring human rhythmic gait movement in the role of cerebral cortex signal

The rhythmic movement is a spontaneous behavior due to the central pattern generator(CPG).At present,the CPG model only shows the spontaneous behavior,butdoes not refer to the instruction regulation role of the cerebral cortex.In this paper,a modified model based on the Matsuoka neural oscillator theory is presented to better show the regulation role of the cerebral cortex signal to the CPG neuronal network.The complex interaction between the in put signal and other parameters in the CPG networkis establish...     

Singularly perturbed nonlinear second order elliptic equation

In this paper, we study singular perturbation problems of some semi-linear second order elliptic equations with nonlinear boundary value conditions: where ε is a small positive parameter and u/ l is a directional derivative, which lies on an oblique vector (x,ε). We have given a construction of the asymptotic solutions and proof of their asymptotic correctness, which is based on the principle of contraction mapping.     

多自由度仿生推进系统的CPG控制

为了提高航行稳定性和机动性而设计的四尾鳍组合推进水下航行器,尾鳍运动自由度众多且相互耦合,稳定且快速的控制方案对提高航行器的整体性能至关重要。本文根据尾鳍运动特点,建立了中枢模式发生器(CPG)模型,协调控制8个驱动舵机,实现巡游、倒退、偏航、俯仰等各种航行状态下尾鳍的组合运动;通过陀螺仪监测航行器的偏航角与俯仰角,形成反馈信号引入CPG模型,对尾鳍运动进行反馈控制,进一步提高了航行稳定性。     

Modelling of thrust generated by oscillation caudal fin of underwater bionic robot

A simplified model of the thrust force is proposed based on a caudal fin oscillation of an underwater bionic robot. The caudal fin oscillation is generalized by central pattern generators (CPGs). In this model, the drag coefficient and lift coefficient are the two critical parameters which are obtained by the digital particle image velocimetry (DPIV) and the force transducer experiment. Numerical simulation and physical experiments have been performed to verify this dynamic model.     

Bifurcation and chaos of a simple walking model driven by a rhythmic signal

The walk of animals is achieved by the interaction between the dynamics of their mechanical system and the central pattern generator (CPG). In this paper, we analyze dynamic properties of a simple walking model of a biped robot driven by a rhythmic signal from an oscillator. In particular, we examine the long-term global behavior and the bifurcation of the motion that leads to chaotic motion, depending on the model parameter values. The simple model consists of a hip and two legs connected at the hip through a rotational joint. The joint is driven by a rhythmic signal from an oscillator, which is an open loop. In order to analyze the bifurcation, we first obtained approximate solutions of the walking motion and then constructed discrete dynamics using the Poincaré map. As a result, we found that consecutive period-doubling bifurcations occur as the model parameter values change, and that the walking motion leads to chaotic motion over the critical value of the model parameters. Moreover, we approximately obtained the period-doubling solutions and the critical value by employing a Newton-Raphson method. Our analytical results were verified by the numerical simulations.     

Self-stability of a simple walking model driven by a rhythmic signal

In this paper, we analyzed the dynamic properties of a simple walking model of a biped robot driven by a rhythmic signal from an oscillator. The oscillator receives no sensory feedback and the rhythmic signal is an open loop. The simple model consists of a hip and two legs that are connected at the hip. The leg motion is generated by a rhythmic signal. In particular, we analytically examined the stability of a periodic walking motion. We obtained approximate periodic solutions and the Jacobian matrix of a Poincaré map by the power-series expansion using a small parameter. Although the analysis was inconclusive when we used only the first order expansion, by employing the second order expansion it clarified the stability, revealing that the periodic walking motion is asymptotically stable and the simple model possesses self-stability as an inherent dynamic characteristic in walking. We also clarified the stability region with respect to model parameters such as mass ratio and walking speed.     

Control strategy of optimal deployment for spacecraft solar array system with initial state uncertainty

A control strategy combining feedforward control and feedback control is presented for the optimal deployment of a spacecraft solar array system with the initial state uncertainty. A dynamic equation of the spacecraft solar array system is established under the assumption that the initial linear momentum and angular momentum of the system are zero. In the design of feedforward control, the dissipation energy of each revolute joint is selected as the performance index of the system. A Legendre pseudospectral method (LPM) is used to transform the optimal control problem into a nonlinear programming problem. Then, a sequential quadratic programming algorithm is used to solve the nonlinear programming problem and offline generate the optimal reference trajectory of the system. In the design of feedback control, the dynamic equation is linearized along the reference trajectory in the presence of initial state errors. A trajectory tracking problem is converted to a two-point boundary value problem based on Pontryagin’s minimum principle. The LPM is used to discretize the two-point boundary value problem and transform it into a set of linear algebraic equations which can be easily calculated. Then, the closed-loop state feedback control law is designed based on the resulting optimal feedback control and achieves good performance in real time. Numerical simulations demonstrate the feasibility and effectiveness of the proposed control strategy.