Control of tool-workpiece interaction force is of vital importance in automated assembly. Using a simple linear continuous model of an edge-following system to predict the appropriate accomodation gains in a force con...
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Control of tool-workpiece interaction force is of vital importance in automated assembly. Using a simple linear continuous model of an edge-following system to predict the appropriate accomodation gains in a force control loop, previous work has shown that force control by accomodation is feasible. Following up this work, this paper describes the analysis, simulation and implementation of an adaptive force control in a two-dimensional edge-following task with a PUMA 560 robot and wrist force sensor. First, a discrete-time model of an edge-following system is developed and then used as the plant; second, a model reference adaptive control (MRAC) scheme is applied to achieve both tracking and regulation purposes. The reference (tracking) model can be determined by experimental reference input and desired model output information; the reference (regulation) model can be obtained by simulation to smooth out the plant output and improve the augmented filtered plant-model error. Study is done on the values of the adaptation gains in the adaptive mechanism, and hence can be adjusted to insure the best plant output performance.
Local state feedback is used to design a decentralized controller for large-scale linear time-invariant systems. The controller is based on model reduction of the system to the order of the subsystems. A computational...
Local state feedback is used to design a decentralized controller for large-scale linear time-invariant systems. The controller is based on model reduction of the system to the order of the subsystems. A computationally efficient algorithm is presented. A 3-subsystem numerical example is used to illustrate the proposed decentralized controller.
Local state feedback is used to design a decentralized controller for a large-scale linear time-invariant systems. The controller is based on modal aggregation of the system to the order of the subsystems. A computati...
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Local state feedback is used to design a decentralized controller for a large-scale linear time-invariant systems. The controller is based on modal aggregation of the system to the order of the subsystems. A computationally very efficient algorithm is presented. A 3-subsystem numerical example is used to illustrate the controller.
This paper proposes two simple schemes for adaptive control of robot manipulator, to achieve trajectory tracking. The state feedback controller consists of feedforward from the reference position trajectory, feedback ...
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This paper proposes two simple schemes for adaptive control of robot manipulator, to achieve trajectory tracking. The state feedback controller consists of feedforward from the reference position trajectory, feedback from the actual trajectory, and an auxiliary input. The feedforward/feedback controller is different from the state feedback controller in that it consists of feedforward from the reference position, velocity, and acceleration trajectory based on “inverse” dynamics of robot manipulator. The feedforward and feedback gains and the auxiliary input are adapted using adaptive control theory based on Lyapunov's direct method, and using only the local information of the corresponding joint. The proposed control schemes are computationally fast and do not require a priori knowledge of the parameter of the manipulator or the payload. Simulation results are presented in support of the proposed schemes.
While it may not be practical to realize a tentative robot design as an actual robot, there is no question of the practicality of a simulation, ROBOT_S is a program in which the foundation for a comprehensive simulati...
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A memory-based robotic control paradigm which learns relationships between a control effort and a change of state is introduced. It has been used to develop a learning control system which implements step responses in...
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A memory-based robotic control paradigm which learns relationships between a control effort and a change of state is introduced. It has been used to develop a learning control system which implements step responses in one dimension on a robotic gripper, with partial success. It was found that velocity as well as positional feedback were required to complete even simple movements. It is believed that aspects of this approach would readily extend to a tactile sensing system.< >
Real-time expert system techniques and applications to robot manipulator control systems are discussed. A novel type of intelligent controller structure, the expert learning controller prototype ELEC (expert learning ...
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Real-time expert system techniques and applications to robot manipulator control systems are discussed. A novel type of intelligent controller structure, the expert learning controller prototype ELEC (expert learning controller), is developed for the trajectory tracking control in repeat operations. ELEC, acting as an intelligent real-time controller in a closed-loop system, can modify the control series in a human-expert-like manner using the experience of previous operations in order to force the system output to converge to the prespecified desired trajectory. ELEC does not require the knowledge of system models, so it can be used in a fairly wide range of control problems. A numerical example for a two-link robot manipulator is given which shows the satisfactory performance of ELEC.< >
A decentralized adaptive control is proposed to stabilize and track the nonlinear interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive c...
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A decentralized adaptive control is proposed to stabilize and track the nonlinear interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma , proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.< >
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