Optimal control of 2-link underactuated robot manipulator

This paper studies the optimal control problem for planar underactuated robot manipulators with two revolute joints and brakes at the unactuated joints in the presence of gravity. The presence of a brake at an unactuated joint gives rise to two operating modes for that joint: free and braked. As a consequence, there exist two operating modes for a robot manipulator with one unactuated joint and four operating modes for a manipulator with two unactuated joints. Since these systems can change dynamics, they can be regarded as switched dynamical systems. The optimal control problem for these systems is solved using the so-called embedding approach. The main advantages of this technique are that assumptions about the number of switches are not necessary, integer or binary variables do not have to be introduced to model switching decisions between modes, and the optimal switching times between modes are not unknowns of the optimal control problem. As a consequence, the resulting problem is a classical continuous optimal control problem. In this way, a general method for the solution of optimal control problems for switched dynamical systems is obtained. It is shown in this paper that it can deal with nonintegrable differential constraints.

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Discrete-Time LQR and H 2 Damping Control of Flexible Payloads Using a Robot Manipulator With a Wrist-Mounted Force/Torque Sensor

10.1115/imece2000-2404 ◽

2000 ◽

Author(s):

Chunhao Joseph Lee ◽

Constantinos Mavroidis

Keyword(s):

Optimal Control ◽

Discrete Time ◽

Robot Manipulator ◽

Control Design ◽

Degree Of Freedom ◽

Flexible Beam ◽

Torque Sensor ◽

Damping Control ◽

Control Feedback ◽

Six Degree Of Freedom

Abstract This paper presents robust and optimal control methods to suppress vibrations of flexible payloads carried by robotic systems. A new improved estimator in discrete-time H2 optimal control design based on the Kalman Filter predictor form is developed here. Two control design methods using state-space models, LQR and H2 Optimal Design, in discrete-time domain are applied and compared. The manipulator joint encoders and the wrist-mounted six-degree-of-freedom force/torque sensor provide the control feedback. A complete dynamic model of the robot/payload system is taken into account to synthesize the controllers. Experimental verifications of both methods are performed using a Mitsubishi five-degree-of-freedom robot manipulator that carries a flexible beam. It is shown that both methods damp out the vibrations of the payload very effectively.

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Under-Actuated Robot Manipulator Positioning Control Using Artificial Neural Network Inversion Technique

Advances in Artificial Intelligence ◽

10.1155/2012/927905 ◽

2012 ◽

Vol 2012 ◽

pp. 1-6 ◽

Cited By ~ 8

Author(s):

Ali T. Hasan

Keyword(s):

Inverse Dynamics ◽

Robot Manipulator ◽

Positioning Control ◽

Passive Joint ◽

Inversion Technique ◽

Working Space ◽

Neural Network Inversion ◽

Gear Trains ◽

Artificial Neural ◽

Underactuated Robot

This paper is devoted to solve the positioning control problem of underactuated robot manipulator. Artificial Neural Networks Inversion technique was used where a network represents the forward dynamics of the system trained to learn the position of the passive joint over the working space of a 2R underactuated robot. The obtained weights from the learning process were fixed, and the network was inverted to represent the inverse dynamics of the system and then used in the estimation phase to estimate the position of the passive joint for a new set of data the network was not previously trained for. Data used in this research are recorded experimentally from sensors fixed on the robot joints in order to overcome whichever uncertainties presence in the real world such as ill-defined linkage parameters, links flexibility, and backlashes in gear trains. Results were verified experimentally to show the success of the proposed control strategy.

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Optimization in the Design and Control of Robotic Manipulators: A Survey

Applied Mechanics Reviews ◽

10.1115/1.3152423 ◽

1989 ◽

Vol 42 (4) ◽

pp. 117-128 ◽

Cited By ~ 3

Author(s):

S. S. Rao ◽

P. K. Bhatti

Keyword(s):

Optimal Control ◽

Robot Manipulator ◽

Research Effort ◽

Industrial Robot ◽

Load Capacity ◽

Robotic Manipulators ◽

Optimization Techniques ◽

Highly Nonlinear ◽

Manipulator Design ◽

And Control

Robotics is a relatively new and evolving technology being applied to manufacturing automation and is fast replacing the special-purpose machines or hard automation as it is often called. Demands for higher productivity, better and uniform quality products, and better working environments are primary reasons for its development. An industrial robot is a multifunctional and computer-controlled mechanical manipulator exhibiting a complex and highly nonlinear behavior. Even though most current robots have anthropomorphic configurations, they have far inferior manipulating abilities compared to humans. A great deal of research effort is presently being directed toward improving their overall performance by using optimal mechanical structures and control strategies. The optimal design of robot manipulators can include kinematic performance characteristics such as workspace, accuracy, repeatability, and redundancy. The static load capacity as well as dynamic criteria such as generalized inertia ellipsoid, dynamic manipulability, and vibratory response have also been considered in the design stages. The optimal control problems typically involve trajectory planning, time-optimal control, energy-optimal control, and mixed-optimal control. The constraints in a robot manipulator design problem usually involve link stresses, actuator torques, elastic deformation of links, and collision avoidance. This paper presents a review of the literature on the issues of optimum design and control of robotic manipulators and also the various optimization techniques currently available for application to robotics.

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