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

Experimental External Force Estimation Using a Non-Linear Observer for 6 axes Flexible-Joint Industrial Manipulators

This paper proposes a non-linear observer to estimate not only the state (position and velocity) of links but also the external forces exerted by the robot during Friction Stir Welding (FSW) processes. The difficulty of performing this process with a robot lies in its lack of rigidity. In order to ensure a better tracking performance, the data such as real positions, velocities of links and external forces are required. However, those variations are not always measured in most industrial robots. Therefore, in this study, an observer is proposed to reconstruct those necessary parameters by using only measurements of motor side. The proposed observer is carried out on a 6 DOF flexible-joint industrial manipulator used in a FSW process.ANR-2010-SEGI-003-01-COROUSSO, French National Agenc

A Robust Controller Design for Simple Robotic Human Arm

Nowadays, the manipulator of two degrees of freedom (2DOF) has many applications. One is a human arm that may be utilized in robotic rehabilitation. The 2DOF controlled robot manipulator usually acts like human arms. This paper aims to design a robust, stable controller for the upper limb robotic model. A sliding mode control (SMC) approach is proposed to realize stability, tracing accuracy, and robustness for 2DOF robotic manipulator. Based on the general manipulator equation of motion, two SMCs are designed. The first is designed according to the input–output stability constraints. The second is designed according to the adaptive law. Not only the trajectory tracking is guaranteed but also stability is ensured. The stability of the controllers is examined based on Lyapunov stability criteria. The controllers and the robotic arm are formulated analytically. The MATLAB platform is adopted to examine and validate the proposed controller’s performance. The addition of adaptation law in the SMC scheme improves the results for the two designed controllers and shows remarkable trajectory tracking and system stability as well. The improvement rate shows an enhancement of 40.5% and 36.7% for manipulator joints 1 and 2, respectively

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

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

Discrete Robust Control of Robot Manipulators using an Uncertainty and Disturbance Estimator

This article presents the design of a robust observer based on the discrete-time formulation of Uncertainty and Disturbance Estimator (UDE), a well-known robust control technique, for the purpose of controlling robot manipulators. The design results in a complete closed-loop, robust, controller--observer structure. The observer incorporates the estimate of the overall uncertainty associated with the plant, in order to mimic its dynamics, and the control law is generated using an auxiliary error instead of state tracking error. A detailed qualitative and quantitative stability analysis is provided, and simulations are performed on the two-link robot manipulator system. Further, a comparative study with well-known control strategies for robot manipulators is presented. The results demonstrate the efficacy of the proposed technique, with better tracking performance and lower control energy compared to other strategies.Comment: 20 pages, 7 figures, 1 tabl

Disturbance observer enhanced variable gain controller for robot teleoperation with motion capture using wearable armbands

Disturbance observer (DOB) based controller performs well in estimating and compensating for perturbation when the external or internal unknown disturbance is slowly time varying. However, to some extent, robot manipulators usually work in complex environment with high-frequency disturbance. Thereby, to enhance tracking performance in a teleoperation system, only traditional DOB technique is insufficient. In this paper, for the purpose of constructing a feasible teleoperation scheme, we develop a novel controller that contains a variable gain scheme to deal with fast-time varying perturbation, whose gain is adjusted linearly according to human surface electromyographic signals collected from Myo wearable armband. In addition, for tracking the motion of operator’s arm, we derive five-joint-angle data of a moving human arm through two groups of quaternions generated from the armbands. Besides, the radial basis function neural networks and the disturbance observer-based control (DOBC) approaches are fused together into the proposed controller to compensate the unknown dynamics uncertainties of the slave robot as well as environmental perturbation. Experiments and simulations are conducted to demonstrated the effectiveness of the proposed strategy