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At least 37 records · Page 2

Adaptive independent joint control of manipulators - Theory and experiment

The author presents a simple decentralized adaptive control scheme for multijoint robot manipulators based on the independent joint control concept. The proposed control scheme for each joint consists of a PID (proportional integral and differential) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. The static and dynamic couplings that exist between the joint motions are compensated by the adaptive independent joint controllers while ensuring trajectory tracking. The proposed scheme is implemented on a MicroVAX II computer for motion control of the first three joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite strongly coupled, highly nonlinear joint dynamics. The results confirm that the proposed decentralized adaptive control of manipulators is feasible, in spite of strong interactions between joint motions. The control scheme presented is computationally very fast and is amenable to parallel processing implementation within a distributed computing architecture, where each joint is controlled independently by a simple algorithm on a dedicated microprocessor.

Seraji, H.↗

A discrete-time adaptive control scheme for robot manipulators

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

Tarokh, M.↗

A multivariable control scheme for robot manipulators

The article puts forward a simple scheme for multivariable control of robot manipulators to achieve trajectory tracking. The scheme is composed of an inner loop stabilizing controller and an outer loop tracking controller. The inner loop utilizes a multivariable PD controller to stabilize the robot by placing the poles of the linearized robot model at some desired locations. The outer loop employs a multivariable PID controller to achieve input-output decoupling and trajectory tracking. The gains of the PD and PID controllers are related directly to the linearized robot model by simple closed-form expressions. The controller gains are updated on-line to cope with variations in the robot model during gross motion and for payload change. Alternatively, the use of high gain controllers for gross motion and payload change is discussed. Computer simulation results are given for illustration.

Tarokh, M.↗

Control of mechanical systems with rolling constraints: Application to dynamic control of mobile robots

There are many examples of mechanical systems that require rolling contacts between two or more rigid bodies. Rolling contacts engender nonholonomic constraints in an otherwise holonomic system. In this article, we develop a unified approach to the control of mechanical systems subject to both holonomic and nonholonomic constraints. We first present a state space realization of a constrained system. We then discuss the input-output linearization and zero dynamics of the system. This approach is applied to the dynamic control of mobile robots. Two types of control algorithms for mobile robots are investigated: trajectory tracking and path following. In each case, a smooth nonlinear feedback is obtained to achieve asymptotic input-output stability and Lagrange stability of the overall system. Simulation results are presented to demonstrate the effectiveness of the control algorithms and to compare the performane of trajectory-tracking and path-following algorithms.

Sarkar, Nilanjan↗

Adaptive control of space based robot manipulators

For space based robots in which the base is free to move, motion planning and control is complicated by uncertainties in the inertial properties of the manipulator and its load. A new adaptive control method is presented for space based robots which achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. A partition is made of the fifteen degree of freedom system dynamics into two parts: a nine degree of freedom invertible portion and a six degree of freedom noninvertible portion. The controller is then designed to achieve trajectory tracking of the invertible portion of the system. This portion consist of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded, but unpredictable. This portion consist of the position of the robot's base and the position of the reaction wheel.

Walker, Michael W.↗

Intelligent Control of Flexible-Joint Robotic Manipulators

This paper considers the trajectory tracking problem for uncertain rigid-link. flexible.joint manipulators, and presents a new intelligent controller as a solution to this problem. The proposed control strategy is simple and computationally efficient, requires little information concerning either the manipulator or actuator/transmission models and ensures uniform boundedness of all signals and arbitrarily accurate task-space trajectory tracking.

Colbaugh, R.↗

Cartesian control of redundant robots

A Cartesian-space position/force controller is presented for redundant robots. The proposed control structure partitions the control problem into a nonredundant position/force trajectory tracking problem and a redundant mapping problem between Cartesian control input F is a set member of the set R(sup m) and robot actuator torque T is a set member of the set R(sup n) (for redundant robots, m is less than n). The underdetermined nature of the F yields T map is exploited so that the robot redundancy is utilized to improve the dynamic response of the robot. This dynamically optimal F yields T map is implemented locally (in time) so that it is computationally efficient for on-line control; however, it is shown that the map possesses globally optimal characteristics. Additionally, it is demonstrated that the dynamically optimal F yields T map can be modified so that the robot redundancy is used to simultaneously improve the dynamic response and realize any specified kinematic performance objective (e.g., manipulability maximization or obstacle avoidance). Computer simulation results are given for a four degree of freedom planar redundant robot under Cartesian control, and demonstrate that position/force trajectory tracking and effective redundancy utilization can be achieved simultaneously with the proposed controller.

Colbaugh, R.↗

Performance capabilities of a JPL dual-arm advanced teleoperation system

The system comprises: (1) two PUMA 560 robot arms, each equipped with the latest JPL developed smart hands which contain 3-D force/moment and grasp force sensors; (2) two general purpose force reflecting hand controllers; (3) a NS32016 microprocessors based distributed computing system together with JPL developed universal motor controllers; (4) graphics display of sensor data; (5) capabilities for time delay experiments; and (6) automatic data recording capabilities. Several different types of control modes are implemented on this system using different feedback control techniques. Some of the control modes and the related feedback control techniques are described, and the achievable control performance for tracking position and force trajectories are reported. The interaction between position and force trajectory tracking is illustrated. The best performance is obtained by using a novel, task space error feedback technique.

Szakaly, Z. F.↗

A Robust Uniform Control Approach for VTOL Aircraft

We present a uniform control approach for transitioning vertical take-off and landing aircraft. The approach combines several well-understood linear techniques, including robust servomechanism linear quadratic regulation, control allocation, and gain scheduling, to provide a practical control framework that can be used to unify the control design process in all flight regimes. The choice of command variables provides a pilot/operator with a uniform set of intuitive control inputs through all phases of flight while also being easily integrated into autonomous trajectory tracking operations. The control method is applied to the NASA LA-8 aircraft, a tandem tiltwing distributed electric propulsion research vehicle designed at NASA Langley Research Center. The trim envelope of the aircraft is explored and the aircraft control authority analyzed throughout the transition corridor. The uniform control approach is then used to develop reference command tracking controllers for both the longitudinal and lateral-directional dynamics. An example trajectory is simulated to demonstrate how the controller effectively transitions the aircraft from hover to forward flight and vice versa while tracking a desired trajectory.

VTOL↗

Autonomous Guidance of Agile Small-scale Rotorcraft

This report describes a guidance system for agile vehicles based on a hybrid closed-loop model of the vehicle dynamics. The hybrid model represents the vehicle dynamics through a combination of linear-time-invariant control modes and pre-programmed, finite-duration maneuvers. This particular hybrid structure can be realized through a control system that combines trim controllers and a maneuvering control logic. The former enable precise trajectory tracking, and the latter enables trajectories at the edge of the vehicle capabilities. The closed-loop model is much simpler than the full vehicle equations of motion, yet it can capture a broad range of dynamic behaviors. It also supports a consistent link between the physical layer and the decision-making layer. The trajectory generation was formulated as an optimization problem using mixed-integer-linear-programming. The optimization is solved in a receding horizon fashion. Several techniques to improve the computational tractability were investigate. Simulation experiments using NASA Ames 'R-50 model show that this approach fully exploits the vehicle's agility.

Mettler, Bernard↗

A new approach to adaptive control of manipulators

An approach in which the manipulator inverse is used as a feedforward controller is employed in the adaptive control of manipulators in order to achieve trajectory tracking by the joint angles. The desired trajectory is applied as an input to the feedforward controller, and the controller output is used as the driving torque for the manipulator. An adaptive algorithm obtained from MRAC theory is used to update the controller gains to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal enhance closed-loop stability and achieve faster adaptation. Simulation results demonstrate the effectiveness of the proposed control scheme for different reference trajectories, and despite large variations in the payload.

Seraji, H.↗

HYPERSONIC AERODYNAMIC PROBLEMS OF THE FUTURE

Blunt shapes were of interest for the speed regime of ballistic missiles and satellite vehicles, in the main, as a result of the necessity for minimizing convective heating. But as speeds exceed escape speed, the heating due to air radiation assumes an even more important role than does the convective heating. It is shown that this change revives interest in the more slender configurations and that when the speed of a vehicle entering the atmosphere of a planet becomes sufficiently great, it may be economical to decelerate in part by retrorocket rather than entirely by aerodynamic braking. The factors discussed determine the speed limit for which retrorocket braking becomes desirable. The change in the basic characteristics of flow brought about by gas radiation at speeds well in excess of escape speed are then analyzed. It is shown that when the gas radiation energy becomes a significant part of the total energy of the flow, it is no longer possible to analyze aerodynamic flow fields with the assumption that the energy of elemental volumes remains constant, since for such cases a transfer of energy by radiation from one elemental volume to another significantly alters the flow. The increase in complexity in the analytical approaches to the problems of these hypersonic flows necessitates, more than ever, continued experimental research, even though such experiments are exceedingly difficult to perform. Extension of our experimental knowledge of these hypersonic flows is shown to be possible by study of tracked trajectories of bright meteors. Some analyses of meteor tracking data are presented which demonstrate that the tracking camera systems employed at present can provide sufficiently accurate results to yield useful aerodynamic heating information.

SATELLITE↗

Trajectory Generation for Flexible-Joint Space Manipulators

Space manipulator arms often exhibit significant joint flexibility and limited motor torque. Future space missions, including satellite servicing and large structure assembly, may involve the manipulation of massive objects, which will accentuate these limitations. Currently, astronauts use visual feedback on-orbit to mitigate oscillations and trajectory following issues. Large time delays between orbit and Earth make ground teleoperation difficult in these conditions, so more autonomous operations must be considered to remove the astronaut resource requirement and expand robotic capabilities in space. Trajectory planning for autonomous systems must therefore be considered to prevent poor trajectory tracking performance. We provide a model-based trajectory generation methodology that incorporates constraints on joint speed, motor torque, and base actuation for flexible-joint space manipulators while minimizing total trajectory time. Full spatial computer simulation results, as well as physical experiment results with a single-joint robot on an air bearing table, show the efficacy of our methodology.

Space robotics↗

Wire-cell 3D pattern recognition techniques for neutrino event reconstruction in large LArTPCs: algorithm description and quantitative evaluation with MicroBooNE simulation

Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers. Through geometry, time, and drifted charge from multiple readout wire planes, 3D space points with associated charge are reconstructed prior to the pattern recognition stage. Pattern recognition techniques, including track trajectory and dQ/dx (ionization charge per unit length) fitting, 3D neutrino vertex fitting, track and shower separation, particle-level clustering, and particle identification are then applied on these 3D space points as well as the original 2D projection measurements. A deep neural network is developed to enhance the reconstruction of the neutrino interaction vertex. Compared to traditional algorithms, the deep neural network boosts the vertex efficiency by a relative 30% for charged-current ν e interactions. Therefore, this pattern recognition achieves 80–90% reconstruction efficiencies for primary leptons, after a 65.8% (72.9%) vertex efficiency for charged-current ν e (ν μ ) interactions. Based on the resulting reconstructed particles and their kinematics, we also achieve 15-20% energy reconstruction resolutions for charged-current neutrino interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗

An approximate inertial manifold (AIM) based closure for turbulent flows

A closure model for turbulent flows is developed based on a dynamical system theory. An appropriately discretized formulation of the governing equations is considered for this process. The key ingredient is an approximation of the system’s attractor, where all the trajectories in phase space are confined. This approximate inertial manifold based approach provides a path to track trajectories of the system in a lower-dimensional subspace. Unlike conventional coarse-graining approaches, the turbulent field is decomposed into resolved and unresolved dynamics using the properties of the governing equations. The novelty of the approach relies on the reconstruction of the unresolved field constrained by the governing equations. A posteriori tests for homogeneous isotropic turbulence and the Kuramoto–Sivashinsky equation show promising results for considerable dimension reduction with strong convergence properties. The proposed model outperforms the dynamic Smagorinsky model, and the computational overhead is competitive with similar approaches.

97 MATHEMATICS AND COMPUTING↗