Maximum Power Point Tracking Using Indirect Adaptive Control Algorithm and Comparison with Other MPPT Technique

Solar photovoltaic (PV) systems, which generate electricity regarded to be a renewable energy source, have great potential. Compared with the traditional power resources, they develop increasingly swiftly. However, the issue is that the environment varies depending upon on generation of Solar panels. The fundamental problem with a PV system is that, according to varied conditions (i.e., irradiance, ambient temperature, etc.), the quantity of energy that photovoltaic systems generate varies. The continued monitoring of the maximum power point (MPP) is needed to maximize the output of a PV system. In this paper, the maximum power point tracking technique (MPPTS) for a photovoltaic system to retrieve the maximum power from the solar arrays in adverse conditions, including changes in irradiation and temperature on the Voltage-current and Voltage-power characteristics of the photovoltaic array modulus is proposed. An indirect adaptive control technique and evaluated with various maximum power point tracking techniques is also stated. Keywords: photovoltaic, maximum power point, maximum power point tracking, indirect adaptive control.

Stability analysis of adaptive control using fuzzy adapting rate neural emulator: Experimental validation on a thermal process

In this study, an adaptive control based on fuzzy adapting rate for neural emulator of nonlinear systems having unknown dynamics is proposed. The indirect adaptive control scheme is composed by the neural emulator and the neural controller which are connected by an autonomous algorithm inspired from the real-time recurrent learning. In order to ensure stability and faster convergence, a neural controller adapting rate is established in the sense of the continuous Lyapunov stability method. Numerical simulations are included to illustrate the effectiveness of the proposed method. The performance of the proposed control strategy is also demonstrated through an experimental simulation.

A Novel Non-integer Indirect Adaptive Control for Non-integer Order Systems with Non-prior Knowledge

In this study, a new non-integer indirect adaptive control method with reference model is suggested for the class of non-integer order systems. The objective of model reference control is to include the output of the given reference fractional model in tracking the output of a controlled plant by using the concept of on-line goal adaptation. The stability of the closed-loop system is analyzed via the Lyapunov method. Finally, Matlab simulation results are presented to illustrate the effectiveness of the proposed method of indirect fractional model reference adaptive control.