Reduced Active Components Count Electronically Adjustable Fractional-Order Controllers: Two Design Examples

Kapoulea, Stavroula; Bizonis, Vassilios; Bertsias, Panagiotis; Psychalinos, Costas; Elwakil, Ahmed S.; Petráš, Ivo

doi:10.3390/electronics9010063

Cited by 8 publications

(12 citation statements)

References 26 publications

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“…Considering that ω pade = ω c = 10rad/s, the resulting 5th-order transfer function of the controller is given by (17), with the values of coefficients being summarized in Table 2. The gain and phase frequency responses obtained from (17), along with theoretically predicted ones given by dashes, are depicted in the plots of Figure 1, where the efficiency of the Padé approximation is readily obtained.…”

Section: Approximation Of Controller Transfer Functionmentioning

confidence: 99%

“…The gain and phase frequency responses obtained from (17), along with theoretically predicted ones given by dashes, are depicted in the plots of Figure 1, where the efficiency of the Padé approximation is readily obtained. The rational integer-order transfer function in (17) can be implemented by following well-known filter design techniques, including series (e.g., multifeedback schemes) as well the parallel connection of fundamental filter functions. The presented concept is general, in the sense that it is independent of the parameters of the FO-[PD] controller, and from the type of the employed plant, it offers versatility from an implementation point of view.…”

Section: Approximation Of Controller Transfer Functionmentioning

confidence: 99%

“…where λ, µ ∈ R provide the controller with two extra degrees of freedom and thereby, with a better adjustment of its characteristics [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Design of Low-Voltage FO-[PD] Controller for Motion Systems

Malatesta

Kapoulea

Psychalinos

et al. 2021

JLPEA

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Fractional-order controllers have gained significant research interest in various practical applications due to the additional degrees of freedom offered in their tuning process. The main contribution of this work is the analog implementation, for the first time in the literature, of a fractional-order controller with a transfer function that is not directly constructed from terms of the fractional-order Laplacian operator. This is achieved using Padé approximation, and the resulting integer-order transfer function is implemented using operational transconductance amplifiers as active elements. Post-layout simulation results verify the validity of the introduced procedure.

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Section: Approximation Of Controller Transfer Functionmentioning

confidence: 99%

Section: Approximation Of Controller Transfer Functionmentioning

confidence: 99%

See 1 more Smart Citation

Design of Low-Voltage FO-[PD] Controller for Motion Systems

Malatesta

Kapoulea

Psychalinos

et al. 2021

JLPEA

Self Cite

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show abstract

“…There have been several works on the analog circuit realization of the FOPID controller reported in the literature, using analog blocks like Operational Transconductance Amplifier (OTA) [32], [33], CCII [34], Voltage Differencing Current Conveyor (VDCC) [35]. Most of these circuits suffer from drawbacks, such as a high number of active/ passive elements [32], [33], and lack of electronic tunability [34].…”

Section: Introductionmentioning

confidence: 99%

Electronically Tunable ACO Based Fuzzy FOPID Controller for Effective Speed Control of Electric Vehicle

2021

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The phenomenal growth of the Electric Vehicle (EV) technology demands efficient and intelligent control strategies for the propulsion system. In this work, a novel fuzzy fractional order PID (FOPID) controller using Ant Colony Optimization (ACO) algorithm has been proposed to control EV speed effectively. The controller parameters and the fuzzy logic controller's membership functions are tuned and updated in real-time using the multi-objective ACO technique. The proposed controller's speed tracking performance is verified using the new European driving cycle (NEDC) test in the MATLAB-Simulink platform. The proposed controller outperforms the ACO-based fuzzy integer-order PID (IOPID), FOPID, and traditional IOPID controllers. The sensitivity analysis confirms the robustness of the proposed controller for varying parameters of the EV model. The stabilization of EV speed in the presence of external disturbance is also confirmed. In the proposed work, an attempt is made to analyze the system's stability using Matignon's theorem, considering the linearized EV model. The proposed controller gives optimum speed tracking performance compared to the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) based fuzzy FOPID controllers. Additionally, the optimized fuzzy FOPID controller is realized using a secondgeneration current conveyor with extra inputs (EX-CCII) and fractional-order capacitors with electronic tunability. The controller circuit's performance evaluation is carried out in the Cadence Analog Design Environment using GPDK 180 nm CMOS process.

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“…Recently, it was shown that fractional-order controllers result in effectively better control proficiency in comparison with the integer-order counterpart [13][14][15]. However, this control approach has rarely applied on PV/battery systems, and only some simple fractional-order controllers with no stability guarantee have been developed.…”

Section: Introductionmentioning

confidence: 99%

Fractional-Order Fuzzy Control Approach for Photovoltaic/Battery Systems under Unknown Dynamics, Variable Irradiation and Temperature

et al. 2020

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For this paper, the problem of energy/voltage management in photovoltaic (PV)/battery systems was studied, and a new fractional-order control system on basis of type-3 (T3) fuzzy logic systems (FLSs) was developed. New fractional-order learning rules are derived for tuning of T3-FLSs such that the stability is ensured. In addition, using fractional-order calculus, the robustness was studied versus dynamic uncertainties, perturbation of irradiation, and temperature and abruptly faults in output loads, and, subsequently, new compensators were proposed. In several examinations under difficult operation conditions, such as random temperature, variable irradiation, and abrupt changes in output load, the capability of the schemed controller was verified. In addition, in comparison with other methods, such as proportional-derivative-integral (PID), sliding mode controller (SMC), passivity-based control systems (PBC), and linear quadratic regulator (LQR), the superiority of the suggested method was demonstrated.

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Reduced Active Components Count Electronically Adjustable Fractional-Order Controllers: Two Design Examples

Cited by 8 publications

References 26 publications

Design of Low-Voltage FO-[PD] Controller for Motion Systems

Design of Low-Voltage FO-[PD] Controller for Motion Systems

Electronically Tunable ACO Based Fuzzy FOPID Controller for Effective Speed Control of Electric Vehicle

Fractional-Order Fuzzy Control Approach for Photovoltaic/Battery Systems under Unknown Dynamics, Variable Irradiation and Temperature

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