Design of an adaptive controller for a telerobot manipulator

The design of a joint-space adaptive control scheme is presented for controlling the slave arm motion of a dual-arm telerobot system developed at Goddard Space Flight Center (GSFC) to study telerobotic operations in space. Each slave arm of the dual-arm system is a kinematically redundant manipulator with 7 degrees of freedom (DOF). Using the concept of model reference adaptive control (MRAC) and Lyapunov direct method, an adatation algorithm is derived which adjusts the PD controller gains of the control scheme. The development of the adaptive control scheme assumes that the slave arm motion is non-compliant and slowly-varying. The implementation of the derived control scheme does not need the computation of the manipulator dynamics, which makes the control scheme sufficiently fast for real-time applications. Computer simulation study performed for the 7-DOF slave arm shows that the developed control scheme can efficiently adapt to sudden change in payloads while tracking various test trajectories such as ramp or sinusoids with negligible position errors

Feasibility study of robotic neural controllers

The results are given of a feasibility study performed to establish if an artificial neural controller could be used to achieve joint space trajectory tracking of a two-link robot manipulator. The study is based on the results obtained by Hecht-Nielsen, who claims that a functional map can be implemented to a desired degree of accuracy with a three layer feedforward artificial neural network. Central to this study is the assumption that the robot model as well as its parameters values are known

Adaptive self-recurrent wavelet neural network and sliding mode controller/observer for a slider crank mechanism

In this paper, a novel control strategy based on an adaptive Self-Recurrent Wavelet Neural Network (SRWNN) and a sliding mode controller/observer for a slider crank mechanism is proposed. The aim is to reduce the tracking error of the linear displacement of this mechanism while following a specified trajectory. The controller design consists of two parts. The first one is a sliding mode control strategy and the second part is an SRWNN controller. This controller is trained offline first, and then the SRWNN weights are updated online by the adaptive control law. Apart from the hybrid control strategy proposed in this paper, a velocity observer is implemented to replace the use of velocity sensors. The outcomes obtained in the numerical experiment section prove that the smallest tracking error is obtained for the linear and angular displacements in comparison with other strategies found in literature due to the uncertainty and disturbance rejection properties of the sliding mode and the self-recurrent wavelet neural network controllers.Peer ReviewedPostprint (author's final draft

Predictive Adaptive Control of Multiple Robots in Cooperative Motion

In this paper we address the problem of controlling multiple robots manipulating a rigid object cooperatively when the robots and load parameters are uncertain. We propose a controller that takes into account the dynamics of both the load and the manipulators. The linearity of the dynamics of the robots and the load, with respect to the unknown parameters, is exploited during the derivation of the parameter adaptation scheme. In order to design a control and update laws that do not require the measurements of the of the joint accelerations or the load acceleration, the dynamics of both the robots and the load are filtered through a stable first order filter. Then two prediction error vectors are defined as the difference between the measured filtered dynamics and the predicted filtered dynamics of both the robots and the load. The least-squares estimation method is used to estimate the parameters of the multi-robot system from the prediction errors. We then develop a controller that is based on the cancellation of the nonlinearities. The proposed controller guarantees global asymptotic tracking of the robot and load trajectories and also guarantees the asymptotic tracking of the internal forces trajectories

Dynamical Modelling and a Decentralized Adaptive Controller for a 12-Tetrahedral Rolling Robot

The 12-tetrahedral robot is an addressable reconfigurable technology (ART)-based variable geometry truss mechanism with twenty-six extensible struts and nine nodes arranged in a tetrahedral mesh. The robot has the capability of reconfiguring shape and dimension for environment sensing requirements, which makes it suitable for space exploration and environmental perception. In this paper, we have derived a dynamics model and presented a decentralized adaptive controller for a 12-tetrahedral robot. First, the robot is divided into the node and the strut subsystems, and the kinetic and the potential energy are calculated for the two subsystems. Then, the dynamics model is achieved by applying the Lagrangian formalism on the total energy of the robot. Since the dynamics is too complicated for implementing model-based controllers, a two-layer controller is presented to control the robot, in which the planning layer determines gait and trajectory of the robot, and the executive layer adopts the decentralized adaptive control strategy and consists of twenty-six strut controllers. Each strut controller regulates the movement of the corresponding strut without information exchange with other struts. Co-simulations based on ADAMS and Matlab have been conducted to verify the feasibility and effectiveness of the proposed controller

Publications of the Jet Propulsion Laboratory 1989

This bibliography describes and indexes by primary author the externally distributed technical reporting, released during 1989, that resulted from scientific and engineering work performed, or managed, by JPL. Three classes of publications are included: JPL publications in which the information is complete for a specific accomplishment; articles from the quarterly Telecommunications and Data Acquisition (TDA) Progress Report; and articles published in the open literature

Pengaturan Impedansi Adaptif Secara Desentralisasi Untuk Gerakan Compliant Pada Robot

Ketika robot menjalankan tugas untuk melaksanakan gerak yang berhubungan dengan lingkungan, maka gaya interaksi dipengaruhi oleh gaya robot dan gaya yang diberikan lingkungan. Gerakan yang mempertimbangkan bagaimana mengatur hubungan atau kontak antara robot dengan lingkungannya disebut sebagai gerakan compliant (compliant motion). Untuk membangkitkan gerakan compliant, salah satu metoda yang digunakan adalah pengaturan impedansi. Pada pengaturan impedansi diperlukan pengetahuan yang tepat tentang parameter dinamik. Untuk mengatasi ketidaktentuan parameter tersebut digunakan metoda pengaturan adaptif. Pada umumnya metoda pengaturan adaptif yang dilakukan berfokus pada skema desain pengaturan secara terpusat (sentralisasi). Pada skema sentralisasi diperlukan pengetahuan yang tepat tentang struktur model dinamik manipulator, yang dalam prakteknya sangat sulit untuk didapatkan. Dalam Tugas Akhir ini diusulkan suatu skema pengaturan impedansi adaptif secara desentralisasi yang tidak memerlukan pengetahuan yang tepat tentang parameter dan struktur model dinamik robot. Pertama, dibahas teori tentang sistem pengaturan impedansi untuk gerakan compliant secara garis besar dilanjutkan dengan pembahasan mengenai perbedaan pengaturan secara sentralisasi dan desentralisasi. Selanjutnya diberikan pembahasan mengenai pengaturan impedansi adaptif secara desentralisasi dan kestabilannya. Akhirnya, effektifitas dan validitas dari metoda yang dikembangkan diuji dengan simulasi komputer