A comparative study between a high-gain interconnected observer and an adaptive observer applied to IM-based WECS

In this paper, a novel age-structured delayed mathematical model to control Aedes aegypti mosquitoes via Wolbachia-infected mosquitoes is introduced. To eliminate the deadly mosquito-borne diseases such as dengue, chikungunya, yellow fever, and Zika virus, the Wolbachia infection is introduced into the wild mosquito population at every stage. This method is one of the promising biological control strategies. To predict the optimal amount of Wolbachia release, the time varying delay is considered. Firstly, the positiveness of the solution and existence of both Wolbachia present and Wolbachia free equilibrium were discussed. Through linearization, construction of suitable Lyapunov–Krasovskii functional, and linear matrix inequality theory (LMI), the exponential stability is also analyzed. Finally, the simulation results are presented for the real-world data collected from the existing literature to show the effectiveness of the proposed model.

Section: Stability Analysismentioning

confidence: 99%

An LMI Approach-Based Mathematical Model to Control Aedes aegypti Mosquitoes Population via Biological Control

Dianavinnarasi

Raja

Alzabut

et al. 2021

“…As can be seen from the figure, the conventional PID controller is a special case of the PI λ D μ controller. Since λ and μ can vary continuously, the PI λ D μ controller is more flexible than the integer-order PID controller [13,14]. By selecting the values of λ and μ reasonably, the dynamic performance of the fractional-order control system can be better adjusted.…”

Section: Pi λ Controller Designmentioning

confidence: 99%

Current PIλ Control of the Single-Phase Grid Inverter

Yang

Liu

et al. 2021

In a grid-connected power generation system, the grid-connected current of the inverter is sensitive to nonlinear factors such as periodic disturbance of grid voltage, which results in grid-connected current waveform distortion. By establishing a single-phase photovoltaic grid-connected inverter control system model, designing an inverse current fractional-order PI (PIλ or FO-PI) controller and the dynamic and steady-state performance, antidisturbance and grid connection inversion characteristics of the system are simulated and compared under the action of the integer-order PI controller and fractional-order PI controller. The quality of the inverter grid-connected current is analyzed by using the fast Fourier transform (FFT). The simulation results show that the fractional-order control system can reduce the total harmonic distortion (THD) of the grid-connected current and dynamic performance and antidisturbance ability of the improving system while satisfying the steady-state performance indexes.

“…A higher adaptation gain yields to a high gain controller with good performances and tracking properties but poor robustness to unmodeled actuator dynamics [2]. In [3,4] and [5], researchers have discussed the robustness of different architectures and schemes of adaptive controllers [6]. To overcome these limitations [7,8] that adaptive controllers are facing, the L 1 adaptive controller was proposed in [9,10].…”

Section: Introductionmentioning

confidence: 99%

$L_{1}$ Adaptive Fractional Control Optimized by Genetic Algorithms with Application to Polyarticulated Robotic Systems

Maalej

Khlif

Mhiri

et al. 2021

Recently, an adaptive control approach has been proposed. This approach, named L 1 adaptive control, involves the insertion of a low-pass filter at the input of the Model Reference Adaptive Control (MRAC). This controller has been designed to overcome several limitations of classical adaptive controllers such as (i) the initialization of estimated parameters, (ii) the stability problems with high adaptation gains, and (iii) the appropriate parameter excitation. In this paper, a new design of the filter is presented, used for L 1 adaptive control, for which the desired performances are guaranteed (appropriate values of the control during start-up, a high filtering of noises, a reduced time lag, and a reduced energy consumption). Parameters of the new proposed filter have been optimised by genetic algorithms. The proposed L 1 adaptive fractional control is applied to a polyarticulated robotic system. Simulation results show the efficiency of the proposed control approach with respect to the classical L 1 adaptive control in the nominal case and in the presence of a multiplicative noise.