Decentralized adaptive partitioned approximation control of high degrees-of-freedom robotic manipulators considering three actuator control modes

International audiencePartitioned approximation control is avoided in most decentralized control algorithms; however, it is essential to design a feedforward control term for improving the tracking accuracy of the desired references. In addition, consideration of actuator dynamics is important for a robot with high-velocity movement and highly varying loads. As a result, this work is focused on decentralized adaptive partitioned approximation control for complex robotic systems using the orthogonal basis functions as strong approximators. In essence, the partitioned approximation technique is intrinsically decentralized with some modifications. Three actuator control modes are considered in this study: (i) a torque control mode in which the armature current is well controlled by a current servo amplifier and the motor torque/current constant is known, (ii) a current control mode in which the torque/current constant is unknown, and (iii) a voltage control mode with no current servo control being available. The proposed decentralized control law consists of three terms: the partitioned approximation-based feedforward term that is necessary for precise tracking, the high gain-based feedback term, and the adaptive sliding gain-based term for compensation of modeling error. The passivity property is essential to prove the stability of local stability of the individual subsystem with guaranteed global stability. Two case studies are used to prove the validity of the proposed controller: a two-link manipulator and a six-link biped robot

Sliding mode robot control with friction and payload estimation

The paper deals with robust motion control of robotic systems with unknown friction parameters and payload mass. The parameters of the robot arm were considered known with a given precision. To solve the control of the robot with unknown payload mass and friction parameters, sliding mode control algorithm was proposed combined with robust parameter adaptation techniques. Using Lyapunov method it was shown that the resulting controller achieves a guaranteed final tracking accuracy. Simulation results are presented to illustrate the effectiveness and achievable control performance of the proposed scheme

Control strategies for robotic manipulators

This survey is aimed at presenting the major robust control strategies for rigid robot manipulators. The techniques discussed are feedback linearization/Computed torque control, Variable structure compensator, Passivity based approach and Disturbance observer based control. The first one is based on complete dynamic model of a robot. It results in simple linear control which offers guaranteed stability. Variable structure compensator uses a switching/relay action to overcome dynamic uncertainties and disturbances. Passivity based controller make use of passive structure of a robot. If passivity of a feedback system is proved, nonlinearities and uncertainties will not affect the stability. Disturbance observer based controllers estimate disturbances, which can be cancelled out to achieve a nominal model, for which a simple controller can then be designed. This paper, after explaining each control strategy in detail, finally compares these strategies for their pros and cons. Possible solutions to cope with the drawbacks have also been presented in tabular form. © 2012 IEEE

Decentralized Robust Control of Robot Manipulators with Harmonic Drive Transmission and Application to Modular and Reconfigurable Serial Arms

In this paper, we propose a decentralized robust control algorithm for modular and reconfigurable robots (MRRs) based on Lyapunov’s stability analysis and backstepping techniques. In using decentralized control schemes with robot manipulators, each joint is considered as an independent subsystem, and the dynamical effects from the other links and joints are treated as disturbance. However, there exist many uncertainties due to unmodeled dynamics, varying payloads, harmonic drive (HD) compliance, HD complex gear meshing mechanisms, etc. Also, while the reconfigurability of MRRs is advantageous, modifying the configuration will result in changes to the robot dynamics parameters, thereby making it challenging to tune the control system. All the above mentioned disturbances in addition to reconfigurability present a challenge in controlling MRRs. The proposed controller is well-suited for MRR applications because of its simple structure that does not require the exact knowledge of the dynamic parameters of the configurations. Desired tracking performance can be achieved via tuning a limited set of parameters of the robust controller. If the numbers of degrees of freedom are held constant, these parameters are shown to be relatively independent of the configuration, and can be held constant between changes in configuration. This strategy is novel compared to existing MRR control methods. In order to validate the controller performance, experimental setup and results are also presented

Disturbance observer-based neural network control of cooperative multiple manipulators with input saturation

In this paper, the complex problems of internal forces and position control are studied simultaneously and a disturbance observer-based radial basis function neural network (RBFNN) control scheme is proposed to: 1) estimate the unknown parameters accurately; 2) approximate the disturbance experienced by the system due to input saturation; and 3) simultaneously improve the robustness of the system. More specifically, the proposed scheme utilizes disturbance observers, neural network (NN) collaborative control with an adaptive law, and full state feedback. Utilizing Lyapunov stability principles, it is shown that semiglobally uniformly bounded stability is guaranteed for all controlled signals of the closed-loop system. The effectiveness of the proposed controller as predicted by the theoretical analysis is verified by comparative experimental studies

High speed, precision motion strategies for lightweight structures

Research on space telerobotics is summarized. Adaptive control experiments on the Robotic Arm, Large and Flexible (RALF) were preformed and are documented, along with a joint controller design for the Small Articulated Manipulator (SAM), which is mounted on the RALF. A control algorithm is described as a robust decentralized adaptive control based on a bounded uncertainty approach. Dynamic interactions between SAM and RALF are examined. Unstability of the manipulator is studied from the perspective that the inertial forces generated could actually be used to more rapidly damp out the flexible manipulator's vibration. Currently being studied is the modeling of the constrained dynamics of flexible arms

Control System Design for a Centrifuge Motion Simulator Based on a Dynamic Model

This paper presents a dynamic model-based design of a control system and an approach toward a drive selection of a centrifuge motion simulator (CMS). The objective of the presented method is to achieve the desired performance while taking into account the complexity of the control system and the overall device cost An estimation of a dynamic interaction of the interconnected CMS links motions is performed using the suitable inverse dynamics simulation. An algorithm based on the approximate inverse dynamics model is used within the drive selection method. The model of the actuator's mechanical subsystem includes the effective inertia (inertia reflected on the rotor shaft) calculated from the inverse dynamics model. A centralized control strategy based on a computed torque method is considered and compared to traditional decentralized motion controllers To obtain an accurate comparison of the suggested control methods through a realistic simulation, structural natural frequencies of the manipulator links are considered, and the actuator capabilities are taken into account The control system design and simulation methods and the drive selection strategies, presented here for the CMS, are applicable within the general robot manipulator's domain