Model-free adaptive control design using evolutionary-neural compensator
Expert Systems with Applications: An International Journal
IEEE Transactions on Neural Networks
Neural sliding mode control with finite time convergence
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Stable auto-tuning of hybrid adaptive fuzzy/neural controllers for nonlinear systems
Engineering Applications of Artificial Intelligence
Fuzzy Sets and Systems
Perspectives of fuzzy systems and control
Fuzzy Sets and Systems
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Discrete-Time sliding-mode control based on neural networks
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
New Online Self-Evolving Neuro Fuzzy controller based on the TaSe-NF model
Information Sciences: an International Journal
| Hi-index | 0.00 |
In direct adaptive control, the adaptation mechanism attempts to adjust a parameterized nonlinear controller to approximate an ideal controller. In the indirect case, however, we approximate parts of the plant dynamics that are used by a feedback controller to cancel the system nonlinearities. In both cases, "approximators" such as linear mappings, polynomials, fuzzy systems, or neural networks can be used as either the parameterized nonlinear controller or identifier model. In this paper, we present algorithms to tune some of the parameters (e.g., the adaptation gain and the direction of descent) for a gradient-based approximator parameter update law used for a class of nonlinear discrete-time systems in both direct and indirect cases. In our proposed algorithms, the adaptation gain and the direction of descent are obtained by minimizing the instantaneous control energy. We will show that updating the adaptation gain can be viewed as a special case of updating the direction of descent. We will also compare the direct and indirect adaptive control schemes and illustrate their performance via a simple surge tank example.