Robust Control of a Flexible Manipulator Arm: A Benchmark Problem

Moberg, Stig; Öhr, Jonas

doi:10.3182/20050703-6-cz-1902.00967

Cited by 12 publications

(7 citation statements)

References 6 publications

(6 reference statements)

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“…For example, this model is used in refs. [3,38,40] and [41] to represent the elasticity of gear boxes in industrial robots. In the work 42 also the validation of this model with reference to an ABB IRB6600 industrial robot is provided.…”

Section: Numerical Results: Constrained Trajectory For the Nominal Symentioning

confidence: 99%

Optimal trajectory planning for nonlinear systems: robust and constrained solution

Boscariol

Gasparetto

2014

Robotica

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This paper presents a solution to the problem of generating constrained robust trajectory\ud planning for nonlinear plants. By using an indirect variational solution method, the necessary\ud optimality conditions deriving from the Pontryagin’s minimum principle are imposed, and\ud lead to a differential Two-Point Boundary Value Problem (TPBVP); numerical solution of\ud the latter is accomplished by means of collocation techniques. The robustness to parametric\ud mismatches is obtained trough the use of sensitivity functions, while a hard constraint on\ud actuator effort is obtained using a smoothing technique. Numerical results shows that the\ud robustness can be greatly improved, and that the inclusion of constraints on actuator effort\ud does not affect it

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Section: Numerical Results: Constrained Trajectory For the Nominal Symentioning

confidence: 99%

Optimal trajectory planning for nonlinear systems: robust and constrained solution

Boscariol

Gasparetto

2014

Robotica

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“…In the field of autonomous mobile robots, a unified benchmark framework for evaluating and comparing motion algorithms for autonomous mobile robots and vehicles is introduced in [10]. Focusing exclusively on robotic arms, a control engineering benchmark problem with industrial relevance is presented in [11]. The process is a simulation model of a nonlinear four-masses system, which should be controlled by a discrete-time controller that optimises performance for given robustness requirements.…”

Section: Related Research Workmentioning

confidence: 99%

A Benchmarking Framework for Control Methods of Maritime Cranes Based on the Functional Mockup Interface

Sanfilippo

Hatledal

Pettersen

et al. 2018

IEEE J. Oceanic Eng.

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A benchmark framework for advanced control methods of maritime cranes is presented based on the use of the Functional Mockup Interface (FMI). The system integrates different manipulator models, all the corresponding hydraulic systems, various vessels, and the surrounding environment for visualisation. Different control methods can be transparently implemented and tested. A set of routine tests, different cost functions and metrics are provided -taking into account several factors, including position accuracy, energy consumption, quality, and safety for both the cranes and the surrounding environment. The concept of operation profiles (OP) is introduced, allowing for definition of different standard transporting and lifting operations. By considering task-oriented routines, this benchmark suite allows the comparison of different control methods independently from the specific crane model to be controlled.Two alternative control methods for maritime cranes based on the use of artificial intelligence (AI) are extensively compared. The first method is based on the use of genetic algorithms (GA), while the second method involves the use of particle swarm optimisation (PSO). Simulation results are presented for both methods.

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“…For a more precise comparison, other norms in the sense of L 1 or L 2 might be required. Recently, a realistic benchmark problem for robust robot control was developed in [16].…”

Section: Motormentioning

confidence: 99%

Precision Control of Robots with Harmonic Drives

Zhu

2007

Proceedings 2007 IEEE International Conference on Robotics and Automation

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Aimed at achieving ultra-high precision control performance for high-end applications of robots equipped with harmonic drives, an adaptive joint torque controller developed previously is extended to all the joints of a seven degrees of freedom (DOF) robot manipulator using four different types of harmonic drives. The developed adaptive joint torque controller uses additional sensing including the joint and motor positions and the joint torque, and adaptively compensates the large friction associated with harmonic drives, while incorporating the dynamics of flexspline. With guaranteed L2/L∞ stability and asymptotic stability, the adaptive joint torque controller allows any motion controller to be employed. Experimental results using the developed adaptive joint torque controller incorporating a motion controller based on the virtual decomposition control demonstrate precision trajectory tracking control of a 7-DOF robot at both moderate and ultra-low speeds. The precision control with encoder-resolution accuracy at an ultralow joint speed of 0.001 (rad/s) characterizes the effectiveness of the friction compensation.

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Robust Control of a Flexible Manipulator Arm: A Benchmark Problem

Cited by 12 publications

References 6 publications

Optimal trajectory planning for nonlinear systems: robust and constrained solution

Optimal trajectory planning for nonlinear systems: robust and constrained solution

A Benchmarking Framework for Control Methods of Maritime Cranes Based on the Functional Mockup Interface

Precision Control of Robots with Harmonic Drives

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