Robust tuning of robot control systems

The computed torque control problem is examined for a robot arm with flexible, geared, joint drive systems which are typical in many industrial robots. The standard computed torque algorithm is not directly applicable to this class of manipulators because of the dynamics introduced by the joint drive system. The proposed approach to computed torque control combines a computed torque algorithm with torque controller at each joint. Three such control schemes are proposed. The first scheme uses the joint torque control system currently implemented on the robot arm and a novel form of the computed torque algorithm. The other two use the standard computed torque algorithm and a novel model following torque control system based on model following techniques. Standard tasks and performance indices are used to evaluate the performance of the controllers. Both numerical simulations and experiments are used in evaluation. The study shows that all three proposed systems lead to improved tracking performance over a conventional PD controller

Experiments in identification and control of flexible-link manipulators

Interest in the study of flexible-link manipulators for space-based applications has risen strongly in recent years. Moreover, numerous experimental results have appeared for the various problems in the modeling, identification and control of such systems. Nevertheless, relatively little literature has appeared involving laboratory verification of tuning controllers for certain types of realistic flexible-link manipulators. Specifically flexible-link manipulators which are required to maintain endpoint accuracy while manipulating loads that are possibly unknown and varying as they undergo disturbance effects from the environment and workspace. Endpoint position control of flexible-link manipulators in these areas are discussed, with laboratory setups consisting of one and two-link manipulators

Parameter identification and model based control of direct drive robots

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NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE

Robust control of geared and direct-drive robotic manipulators under parameter and model uncertainties

Thesis (M.S.) University of Alaska Fairbanks, 2005The major contribution of this thesis is the design and evaluation of a chattering-free sliding mode controller (SMC), which is a novel application for 2 degree-of-freedom (DOF) planar robot arms exposed to load variations. The performance of the SMC is evaluated in comparison to a proportional-derivative-plus (PD+) controller, as an example of nonlinear model-based controllers, as well as classical linear controllers, such as proportional-derivative (PD) and proportional-integral-derivative (PID). The performance of all four methods has been tested via realistic and detailed simulation models developed for both geared and direct-drive type 2-DOF planar robot arms. The model used in simulations reflects the dynamics of the arm, as well as the actuator dynamics and pulse width modulation (PWM) switching of the power converters. Simulations are performed under unknown load variations for both step and sinusoidal type reference joint trajectories. The results demonstrate that the chattering-free SMC provides increased accuracy and robustness than that of the other controllers and requires no prior knowledge of the system dynamic model and the load variation that the end-effector is subjected to. The results obtained could be extended to the control of a variety of geared and direct-drive type robotic configurations.Introduction -- Modeling of 2-DOF planar elbow manipulator -- Control of 2-DOF planar elbow manipulator -- Simulation results -- Conclusions and future work -- References -- Appendix

Controlling under-actuated robot arms using a high speed dynamics process

The invention controls an under-actuated manipulator by first obtaining predetermined active joint accelerations of the active joints and the passive joint friction forces of the passive joints, then computing articulated body qualities for each of the joints from the current positions of the links, and finally computing from the articulated body qualities and from the active joint accelerations and the passive joint forces, active joint forces of the active joints. Ultimately, the invention transmits servo commands to the active joint forces thus computed to the respective ones of the joint servos. The computation of the active joint forces is accomplished using a recursive dynamics algorithm. In this computation, an inward recursion is first carried out for each link, beginning with the outermost link in order to compute the residual link force of each link from the active joint acceleration if the corresponding joint is active, or from the known passive joint force if the corresponding joint is passive. Then, an outward recursion is carried out for each link in which the active joint force is computed from the residual link force if the corresponding joint is active or the passive joint acceleration is computed from the residual link force if the corresponding joint is passive

DYNAMIC MODEL WITH A NEW FORMULATION OF CORIOLIS/CENTRIFUGAL MATRIX FOR ROBOT MANIPULATORS

The paper presents a complete generalized procedure based on the Euler-Lagrange equations to build the matrix form of dynamic equations, called dynamic model, for robot manipulators. In addition, a new formulation of the Coriolis/centrifugal matrix is proposed. The link linear and angular velocities are formulated explicitly. Therefore, the translational and rotational Jacobian matrices can be derived straightforward from definition, which makes the calculation of the generalized inertia matrix more convenient. By using Kronecker product, a new Coriolis/centrifugal matrix formulation is set up directly in matrix-based manner and guarantees the skew symmetry property of robot dynamic equations. This important property is usually exploited for developing many control methodologies. The validation of the proposal formulation is confirmed through the symbolic solution and simulation of a typical robot manipulator

COMPUTED TORQUE CONTROL FOR A SPATIAL DISORIENTATION TRAINER

A development of a robot control system is a highly complex task due to nonlinear dynamic coupling between the robot links. Advanced robot control strategies often entail difficulties in implementation, and prospective benefits of their application need to be analyzed using simulation techniques. Computed torque control (CTC) is a feedforward control method used for tracking of robot’s time-varying trajectories in the presence of varying loads. For the implementation of CTC, the inverse dynamics model of the robot manipulator has to be developed. In this paper, the addition of CTC compensator to the feedback controller is considered for a Spatial disorientation trainer (SDT). This pilot training system is modeled as a 4DoF robot manipulator with revolute joints. For the designed mechanical structure, chosen actuators and considered motion of the SDT, CTC-based control system performance is compared with the traditional speed PI controller using the realistic simulation model. The simulation results, which showed significant improvement in the trajectory tracking for the designed SDT, can be used for the control system design purpose as well as within mechanical design verification

Computed torque control for a spatial disorientation trainer

A development of a robot control system is a highly complex task due to nonlinear dynamic coupling between the robot links. Advanced robot control strategies often entail difficulties in implementation, and prospective benefits of their application need to be analyzed using simulation techniques. Computed torque control (CTC) is a feed-forward control method used for tracking of robot's time-varying trajectories in the presence of varying loads. For the implementation of CTC, the inverse dynamics model of the robot manipulator has to be developed. In this paper, the addition of CTC compensator to the feedback controller is considered for a Spatial disorientation trainer (SDT). This pilot training system is modeled as a 4DoF robot manipulator with revolute joints. For the designed mechanical structure, chosen actuators and considered motion of the SDT, CTC-based control system performance is compared with the traditional speed PI controller using the realistic simulation model. The simulation results, which showed significant improvement in the trajectory tracking for the designed SDT, can be used for the control system design purpose as well as within mechanical design verification