Abstract
In this paper, the basic theory of the model reference adaptive control design and issues of particular relevance to control nonlinear dynamic plants with a relative degree greater than or equal to one with unknown parameters are detailed. The studied analysis was motivated through its application to a robot manipulator with six degrees of freedom. After linearization using the input-output feedback linearization and decoupling algorithm, the nonlinear Multi-input Multi-output system was transformed into six independent single-input single-output linear subsystems each one has a relative degree equal to two, the obtained results in different simulations shows that the augmented reference model adaptive controller has been successfully implemented.
Highlights
Nowadays, a great performance of industrial control systems are under adaptive control techniques [1], these include a high scale of tasks in aerospace, robotics, process control, ship steering, and automotive and biomedical plants.Specially, for robotic control, a control designer can be faced with joint flexibilities, unknown manipulator dynamic parameters, nonlinear joint interactions, and dynamics changing due to unknown and varying loads
The model reference adaptive control system (MRAC) was initially developed to adjust the problems in which the performance specifications are given in terms of a reference model [1, 3, 4]
A nonlinear six degrees of freedom robot manipulator model is employed to demonstrate the performance of the proposed MRAC approche, which is a serial open chain composed of seven rigid links connected with six rotoïde joints as discussed in our recent works [11, 12, 13]
Summary
A great performance of industrial control systems are under adaptive control techniques [1], these include a high scale of tasks in aerospace, robotics, process control, ship steering, and automotive and biomedical plants. When a designer has limited knowledge of these parameters and interactions, it can be advantageous to exploit adaptive control approaches to reduce the effects of these problems. The model reference adaptive control system (MRAC) was initially developed to adjust the problems in which the performance specifications are given in terms of a reference model [1, 3, 4]. This model tells how the process output ideally should deal to the command signal.
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