Engineering topics

Yae, K. Harold

Publications and source records attributed to Yae, K. Harold.

5 records

NASA NTRS1989

Recursive linearization of multibody dynamics equations of motion

The equations of motion of a multibody system are nonlinear in nature, and thus pose a difficult problem in linear control design. One approach is to have a first-order approximation through the numerical perturbations at a given configuration, and to design a control law based on the linearized model. Here, a linearized model is generated analytically by following the footsteps of the recursive derivation of the equations of motion. The equations of motion are first written in a Newton-Euler form, which is systematic and easy to construct; then, they are transformed into a relative coordinate representation, which is more efficient in computation. A new computational method for linearization is obtained by applying a series of first-order analytical approximations to the recursive kinematic relationships. The method has proved to be computationally more efficient because of its recursive nature. It has also turned out to be more accurate because of the fact that analytical perturbation circumvents numerical differentiation and other associated numerical operations that may accumulate computational error, thus requiring only analytical operations of matrices and vectors. The power of the proposed linearization algorithm is demonstrated, in comparison to a numerical perturbation method, with a two-link manipulator and a seven degrees of freedom robotic manipulator. Its application to control design is also demonstrated.

Lin, Tsung-Chieh↗

NASA NTRS1989

Experimental verification of dynamic simulation

The dynamics model here is a backhoe, which is a four degree of freedom manipulator from the dynamics standpoint. Two types of experiment are chosen that can also be simulated by a multibody dynamics simulation program. In the experiment, recorded were the configuration and force histories; that is, velocity and position, and force output and differential pressure change from the hydraulic cylinder, in the time domain. When the experimental force history is used as driving force in the simulation model, the forward dynamics simulation produces a corresponding configuration history. Then, the experimental configuration history is used in the inverse dynamics analysis to generate a corresponding force history. Therefore, two sets of configuration and force histories--one set from experiment, and the other from the simulation that is driven forward and backward with the experimental data--are compared in the time domain. More comparisons are made in regard to the effects of initial conditions, friction, and viscous damping.

Yae, K. Harold↗

NASA NTRS1989

Man-in-the-control-loop simulation of manipulators

A method to achieve man-in-the-control-loop simulation is presented. Emerging real-time dynamics simulation suggests a potential for creating an interactive design workstation with a human operator in the control loop. The recursive formulation for multibody dynamics simulation is studied to determine requirements for man-in-the-control-loop simulation. High speed computer graphics techniques provides realistic visual cues for the simulator. Backhoe and robot arm simulations are implemented to demonstrate the capability of man-in-the-control-loop simulation.

Chang, J. L.↗

NASA NTRS1989

Model reduction in the physical coordinate system

In the dynamics modeling of a flexible structure, finite element analysis employs reduction techniques, such as Guyan's reduction, to remove some of the insignificant physical coordinates, thus producing a dynamics model that has smaller mass and stiffness matrices. But this reduction is limited in the sense that it removes certain degrees of freedom at a node points themselves in the model. From the standpoint of linear control design, the resultant model is still too large despite the reduction. Thus, some form of the model reduction is frequently used in control design by approximating a large dynamical system with a fewer number of state variables. However, a problem arises from the placement of sensors and actuators in the reduced model, because a model usually undergoes, before being reduced, some form of coordinate transformations that do not preserve the physical meanings of the states. To correct such a problem, a method is developed that expresses a reduced model in terms of a subset of the original states. The proposed method starts with a dynamic model that is originated and reduced in finite element analysis. Then the model is converted to the state space form, and reduced again by the internal balancing method. At this point, being in the balanced coordinate system, the states in the reduced model have no apparent resemblance to those of the original model. Through another coordinate transformation that is developed, however, this reduced model is expressed by a subset of the original states.

Yae, K. Harold↗

NASA NTRS1989

Test and validation for robot arm control dynamics simulation

The Flight Telerobotic Servicer (FTS) program will require an ability to develop, in a cost effective manner, many simulation models for design, analysis, performance evaluation, and crew training. Computational speed and the degree of modeling fidelity associated with each simulation must be commensurate with problem objectives. To demonstrate evolving state-of-the-art general purpose multibody modeling capabilities, to validate these by laboratory testing, and to expose their modeling shortcomings, two focus problems at the opposite ends of the simulation spectrum are defined: (1) Coarse Acquisition Control Dynamics. Create a real time man-in-the-control-loop simulator. Provide animated graphical display of robot arm dynamics and tactile feedback sufficient for cueing the operator. Interface simulator software with human operated tactile feedback controller; i.e., the Kraft mini-master. (2) Fine, Precision Mode Control Dynamics. Create a high speed, high fidelity simulation model for the design, analysis, and performance evaluation of autonomous 7 degree-of-freedom (DOF) trajectory control algorithms. This model must contain detail dynamic models for all significant dynamics elements within the robot arm, such as joint drive mechanisms.

Yae, K. Harold↗