FOMCON: Fractional-Order Modeling and Control Toolbox

Tepljakov, Aleksei

doi:10.1007/978-3-319-52950-9_6

Cited by 112 publications

(119 citation statements)

References 2 publications

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“…U(s) and E(s) are the control and error signals, respectively. In this study, PI λ D μ controller software was performed by FOMCON toolbox [29].…”

Section: Fractional Pid Controller (Pimentioning

confidence: 99%

A Five-Level H-Bridge STATCOM for an Off-Grid PV Solar Farm under Two Controllers PI and PI^λ-MPC Hybrid

Mengi

2018

International Journal of Photoenergy

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Investigations were presented in order to eliminate the reactive power on microgrid loads fed by an off-grid and mid-power photovoltaic solar energy system (PVSES) with a static synchronous compensator (STATCOM) device. The electric network is specifically characterized by P-Q loads, ambient temperature, and widely variable solar radiation levels. Two main innovations are developed. Firstly, the STATCOM apparatus is a 5-level H-bridge inverter with capacitances as load and must totally compensates the reactive power in the network load. Secondly, this compensation is controlled by a set of fractional PI (PI λ ) and model predictive control (MPC) hybrid. The efficiencies of these controllers were compared with classical PI controllers. Large simulations, without and with reactive power compensation, in steady and transient states, are carried out to underline the merits of the presented works, by performing in the MATLAB-Simulink environment.

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“…U(s) and E(s) are the control and error signals, respectively. In this study, PI λ D μ controller software was performed by FOMCON toolbox [29].…”

Section: Fractional Pid Controller (Pimentioning

confidence: 99%

A Five-Level H-Bridge STATCOM for an Off-Grid PV Solar Farm under Two Controllers PI and PI^λ-MPC Hybrid

Mengi

2018

International Journal of Photoenergy

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“…The values of weight functions mentioned in equation (6) are chosen as w 1 = w 2 = 0.6, w 3 = 1. The controller is analyzed and implemented using FOMCON toolbox designed for MATLAB [40]. It supports the simulation, optimization and realization of FOPID controllers via its built-in functions.…”

Section: Fopid Controller Designmentioning

confidence: 99%

Fractional Order Based Computed Torque Control of 2-link Robotic Arm

Anwaar¹,

Yin²,

Ijaz³

et al. 2018

Adv. Sci. Technol. Res. J.

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The paper proposes the application of fractional order controller in position tracking control of 2-link nonlinear robotic arm. The nonlinear system dynamics is linearized using inverse dynamics of the model and fractional order PID controller is designed to deal with remaining tracking errors. The optimal values of controller parameters are calculated using Nelder-Mead optimization technique based on desired design criteria. The objective function is designed using weighted sum approach on each performance specification based on transient domain parameters. It can be seen from simulation results that fractional order controller together with computed torque controller improved tracking performance of proposed system as compared to PID controller used in the outer loop. Moreover, the robustness of proposed scheme is checked by applying the disturbance signal at control input channels of 2-link nonlinear robotic arm links.

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“…[49]. A square wave signal with a random amplitude is used as an input to the HWFC model, given in Fig.…”

Section: Numerical Studymentioning

confidence: 99%

Parameter estimation of the fractional‐order Hammerstein–Wiener model using simplified refined instrumental variable fractional‐order continuous time

Allafi

Zajic

Uddin

et al. 2017

IET Control Theory & Applications

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This study proposes a direct parameter estimation approach from observed input-output data of a stochastic singleinput-single-output fractional-order continuous-time Hammerstein-Wiener model by extending a well known iterative simplified refined instrumental variable method. The method is an extension of the simplified refined instrumental variable method developed for the linear fractional-order continuous-time system, denoted. The advantage of this novel extension, compared with published methods, is that the static output non-linearity of the Wiener model part does not need to be invertible. The input and output static non-linear functions are represented by a sum of the known basis functions. The proposed approach estimates the parameters of the linear fractional-order continuous-time subsystem and the input and output static non-linear functions from the sampled input-output data by considering the system to be a multi-input-single-output linear fractional-order continuoustime model. These extra inputs represent the basis functions of the static input and output non-linearity, where the output basis functions are simulated according to the previous estimates of the fractional-order linear subsystem and the static input nonlinear function at every iteration. It is also possible to estimate the classical integer-order model counterparts as a special case. Subsequently, the proposed extension to the simplified refined instrumental variable method is considered in the classical integer-order continuous-time Hammerstein-Wiener case. In this paper, a Monte Carlo simulation analysis is applied for demonstrating the performance of the proposed approach to estimate the parameters of a fractional-order Hammerstein-Wiener output model.

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FOMCON: Fractional-Order Modeling and Control Toolbox

Cited by 112 publications

References 2 publications

A Five-Level H-Bridge STATCOM for an Off-Grid PV Solar Farm under Two Controllers PI and PI^λ-MPC Hybrid

A Five-Level H-Bridge STATCOM for an Off-Grid PV Solar Farm under Two Controllers PI and PI^λ-MPC Hybrid

Fractional Order Based Computed Torque Control of 2-link Robotic Arm

Parameter estimation of the fractional‐order Hammerstein–Wiener model using simplified refined instrumental variable fractional‐order continuous time

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FOMCON: Fractional-Order Modeling and Control Toolbox

Cited by 112 publications

References 2 publications

A Five-Level H-Bridge STATCOM for an Off-Grid PV Solar Farm under Two Controllers PI and PIλ-MPC Hybrid

A Five-Level H-Bridge STATCOM for an Off-Grid PV Solar Farm under Two Controllers PI and PIλ-MPC Hybrid

Fractional Order Based Computed Torque Control of 2-link Robotic Arm

Parameter estimation of the fractional‐order Hammerstein–Wiener model using simplified refined instrumental variable fractional‐order continuous time

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Product

Resources

About

A Five-Level H-Bridge STATCOM for an Off-Grid PV Solar Farm under Two Controllers PI and PI^λ-MPC Hybrid

A Five-Level H-Bridge STATCOM for an Off-Grid PV Solar Farm under Two Controllers PI and PI^λ-MPC Hybrid