ANALYTICAL MODEL ALGORITHM FOR DYNAMICS OF ROBOTIC MANIPULATORS

A simple analytical model method for dynamics of robotic manipulators is proposed.Problem of deriving model matrix elements is transformed into problem of solving for driving forceand driving torque under specified condition by recursive dynamic equations. Expressions of reaction force in arbitrary joint in numeric-symbolic form are also derived. The properties of modelmatrices are given. Corresponding software which can recognize and manipulate symbols is developed and can be used to generate model and real-time code of robotic dynamics.

Real-Time Arm Animation with Natural Collision Avoidance

A novel approach to realistic collision-free animation of the upper limb was proposed.According to the obstacle-avoidance strategy of human hand,the movement trajectory was computed by manipulability model and minimum-jerk based interpolation.In each key frame,an improved in～verse kinematics method was adopted to obtain a believable posture of the upper limb.By comparing with the real movement data obtained from the motion capture device,the resultant animation was testified to be natural.This method can be performed in interactive time,and therefore is applicable in animation edit and control of virtual humans.

Sliding mode-based adaptive tube model predictive control for robotic manipulators with model uncertainty and state constraints

In this paper,the optimal tracking control for robotic manipulators with state constraints and uncertain dynamics is investigated,and a sliding mode-based adaptive tube model predictive control method is proposed.First,utilizing the high-order fully actuated system approach,the nominal model of the robotic manipulator is constructed as the predictive model.Based on the nominal model,a nominal model predictive controller with the sliding mode is designed,which relaxes the terminal constraints,and realizes the accurate and stable tracking of the desired trajectory by the nominal system.Then,an auxiliary controller based on the node-adaptive neural networks is constructed to dynamically compensate nonlinear uncertain dynamics of the robotic manipulator.Furthermore,the estimation deviation between the nominal and actual states is limited to the tube invariant sets.At the same time,the recursive feasibility of nominal model predictive control is verified,and the ultimately uniformly boundedness of all variables is proved according to the Lyapunov theorem.Finally,experiments show that the robotic manipulator can achieve fast and efficient trajectory tracking under the action of the proposed method.

Characteristic model-based consensus of networked heterogeneous robotic manipulators with dynamic uncertainties

In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of multiple robotic agents interconnected on directed graphs containing a spanning tree. A novel characteristic model-based distributed adaptive control scenario is proposed with a state-relied projection estimation law and a characteristic model-based distributed controller. The performance analysis is also unfolded where the uniform ultimate boundedness(UUB) of consensus errors is derived by resorting to the discrete-time-domain stability analysis tool and the graph theory. Finally, numerical simulations illustrate the effectiveness of the proposed theoretical strategy.

The kinetics of force-dependent hybridization and strand-peeling of short DNA fragments

Deoxyribonucleic acid(DNA) carries the genetic information in all living organisms. It consists of two interwound single-stranded(ss) strands, forming a double-stranded(ds) DNA with a right-handed double-helical conformation. The two strands are held together by highly specific basepairing interactions and are further stabilized by stacking between adjacent basepairs. A transition from a dsDNA to two separated ssDNA is called melting and the reverse transition is called hybridization. Applying a tensile force to a dsDNA can result in a particular type of DNA melting, during which one ssDNA strand is peeled away from the other. In this work, we studied the kinetics of strand-peeling and hybridization of short DNA under tensile forces. Our results show that the force-dependent strand-peeling and hybridization can be described with a simple two-state model. Importantly, detailed analysis of the force-dependent transition rates revealed that the transition state consists of several basepairs dsDNA.