This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for ha...

Reinforcement Learning methods based on approximating dynamic programming (DP) are receiving increased attention due to their utility in forming reactive control policies for systems embedded in dynamic environments. Environments are usually modeled as controlled Markov processes, but when the environment model is not known a priori, adaptive methods are necessary. Adaptive control methods are ...

A new hybrid direct/indirect adaptive fuzzy neural network (FNN) controller with a state observer and supervisory controller for a class of uncertain nonlinear dynamic systems is developed in this paper. The hybrid adaptive FNN controller, the free parameters of which can be tuned on-line by an observer-based output feedback control law and adaptive law, is a combination of direct and indirect ...

This paper shows implementation of indirect adaptive control law for nonlinear systems using TakagiSugeno fuzzy system. Takagi-Sugeno fuzzy system is used to identify nonlinear system components theta alpha and theta beta. Stable Indirect Adaptive control law is such that it has two control components one is certainty equivalence control and other is sliding mode control. Sliding mode controlle...

For indirect adaptive fuzzy ∞ H tracking control (AFHC) of perturbed uncertain nonlinear systems, slidingmode control (SMC) compensation usually has to be applied to ensure stability and ∞ H robustness of the closed-loop system. We prove that indirect AFHC without SMC compensation is sufficient to guarantee stable ∞ H tracking under given initial conditions and parameter constraints. The contro...

The paper presents how to design the indirect vector control of three-phase induction motor drive systems using the artificial intelligence technique called the adaptive tabu search. The results from the simulation and the experiment show that the drive system with the controller designed from the proposed method can provide the best output speed response compared with those of the conventional...

To control quarter-car systems, a novel indirect adaptive interval type-2 Fuzzy Neural Network (FNN) controller is developed in this paper to achieve both ride comfort and good handling. By incorporating indirect adaptive interval type-2 FNN control approach and sliding mode control, car suspension system regulation performance can be achieved based on Lyapunov stability criterion. The simulati...