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Modeling of pine sleek PID control system in AC heat exchanger

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Abstract

The heat exchanger system (HES) of an air conditioner (AC) has difficulty in maintaining the proper output temperature during heat exchange in the existing system. Therefore, a controller has been created to control this outlet procedure in HES. However, it has major vibrations, heat and exchanger leakages, energy consumption, fouling, and other difficulties that cause it to overheat. To achieve optimal tuning, a mixture of gases, pressure, and humidity must be optimized. Thus, to achieve the exact solution, the paper proposes a novel pine sleek PID (PSP) controller that uses fuzzy logic in the adaption of Gaussian member functions and a multivariable exponential method to eliminate vibration and thermal exchanger leakages. Also, the integral square error (ISE) was optimized using the global optimization principle of the Luus–Jaakola (LJ) algorithm, which reduces energy usage and minimizes the error. Meanwhile, to optimize the maximum peak value with the shorter feedback process, it controls the various factors to get the desired temperature. In comparison to the previous technique, the proposed technique achieves a peak time of 1.0 s, which is 0.8 s faster than the auto-tuned PID. As a result, the proposed method effectively provides a PID control system in an AC heat exchanger with the largest peak value in the smallest time, proving efficiency.

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Abbreviations

LJ:

Luus–Jaakola algorithm

\({R}_{\mathrm{t}}\) :

Room temperature

\({K}_{\mathrm{d}}\) :

Derivative gain

\({K}_{\mathrm{p}}\) :

Probability gain

\({K}_{\mathrm{i}}\) :

Integral gain

\(e(t)\) :

Error

ISE:

Integral square error

HES:

Heat exchanger system

PID:

Proportional-integral-derivative

PSP:

Pine sleek PID

\({K}^{\mathrm{G}}\) :

Gaussian gain

\(\sigma\) :

Pressure range

c :

Range for a mixture of gasses

References

  • Abdelrahim EM (2021) Hierarchical adaptive genetic algorithm based T-S fuzzy controller for non-linear automotive applications. Int J Fuzzy Syst 24(1):607–621

    Article  Google Scholar 

  • AbouOmar MS, Hua-Jun Z, Su Y-X (2019) Fractional order fuzzy PID control of automotive PEM fuel cell air feed system using neural network optimization algorithm. Energies 12(8):1435

    Article  Google Scholar 

  • Aguitoni MC, Leandro VP, da Silva Sá Ravagnani MA (2019) Heat exchanger network synthesis combining simulated annealing and differential evolution. Energy 181:654–664

    Article  Google Scholar 

  • Aly M, Rezk H (2021) An improved fuzzy logic control-based MPPT method to enhance the performance of PEM fuel cell system. Neural Comput Appl 34(6):4555–4566

    Article  Google Scholar 

  • Bastida H, Ugalde-Loo CE, Abeysekera M, Xu X, Qadrdan M (2019) Dynamic modeling and control of counter-flow heat exchangers for heating and cooling systems. In: 2019 54th international universities power engineering conference (UPEC), pp 1–6

  • Bharath Kumar V, Sampath D, Praneeth VNS, Pavan Kumar YV (2021) Error performance index based PID tuning methods for temperature control of heat exchanger system. In: IEEE international IOT, electronics and mechatronics conference (IEMTRONICS)

  • Davoudi E, Vaferi B (2018) Applying artificial neural networks for systematic estimation of degree of fouling in heat exchangers. Chem Eng Res Des 130:138–153

    Article  Google Scholar 

  • Esapour M, Hamzehnezhad A, Darzi AAR, Jourabian M (2018) Melting and solidification of PCM embedded in porous metal foam in horizontal multi-tube heat storage system. Energy Convers Manage 171:398–410

    Article  Google Scholar 

  • Ji W, Qiu J, Wu L, Lam H-K (2019) Fuzzy-affine-model-based output feedback dynamic sliding mode controller design of nonlinear systems. IEEE Trans Syst Man Cybern Syst 51(3):1652–1661

    Google Scholar 

  • Júnior Paulo RM, Allan Cupertino F, Gabriel Mendonça A, Heverton Pereira A (2019) On lifetime evaluation of medium-voltage drives based on modular multilevel converter. IET Electr Power Appl 13(10):1453–1461

    Article  Google Scholar 

  • Kuyuk AF, Ghoreishi-Madiseh SA, Hassani PF (2020) Closed-loop bulk air conditioning: a renewable energy-based system for deep mines in arctic regions. Int J Min Sci Technol 30(4):511–516

    Article  Google Scholar 

  • Liu Z, Chen H, Peng L, Ye X, Xu S, Zhang T (2021) Feedforward-decoupled closed-loop fuzzy proportion-integral-derivative control of air supply system of proton exchange membrane fuel cell. Energy 240:122490

    Article  Google Scholar 

  • Luo D, Wang R, Yu W, Zhou W (2020a) A numerical study on the performance of a converging thermoelectric generator system used for waste heat recovery. Appl Energy 270:115181

    Article  Google Scholar 

  • Luo L, Wu Z, Gu W, Huang H, Gao S, Han J (2020b) Coordinated allocation of distributed generation resources and electric vehicle charging stations in distribution systems with vehicle-to-grid interaction. Energy 192:116631

    Article  Google Scholar 

  • Oravec J, Bakošová M, Mészáros A, Míková N (2016) Experimental investigation of alternative robust model predictive control of a heat exchanger. Appl Therm Eng 105:774–782

    Article  Google Scholar 

  • Pavković D, Šprljan P, Cipek M, Krznar M (2021) Cross-axis control system design for borehole drilling based on damping optimum criterion and utilization of proportional-integral controllers. Optim Eng 22(1):51–81

    Article  MathSciNet  Google Scholar 

  • Pham HA, Söffker D (2019) Model-free adaptive control method applied to vibration reduction of a flexible crane as MIMO system. PAMM 19(1):e201900145

    Article  Google Scholar 

  • Pradityo F, Surantha N (2019) Indoor air quality monitoring and controlling system based on IoT and fuzzy logic. In: 2019 7th international conference on information and communication technology (ICoICT), pp 1–6

  • Sabir MM, Ali T (2016) Optimal PID controller design through swarm intelligence algorithms for sun tracking system. Appl Math Comput 274:690–699

    MathSciNet  Google Scholar 

  • Tridianto E et al (2017) Cascaded PID temperature controller for FOPDT model of shell-and-tube heat exchanger based on Matlab/Simulink. In: 2017 international electronics symposium on engineering technology and applications (IES-ETA). IEEE

  • Vasičkaninová A, Bakošová M (2015) Control of a heat exchanger using neural network predictive controller combined with auxiliary fuzzy controller. Appl Therm Eng 89:1046–1053

    Article  Google Scholar 

  • Vivek D (2021) PID controller design with cuckoo search algorithm for stable and unstable SOPDT processes. IOP Conf Ser Mater Sci Eng 1091(1):012059

    Article  Google Scholar 

  • Wang T, Gao H, Qiu J (2016) A combined adaptive neural network and nonlinear model predictive control for multirate networked industrial process control. IEEE Trans Neural Netw Learn Syst 27(2):416–425

    Article  MathSciNet  Google Scholar 

  • Yeudiel G, Best R, Gómez VH, Vargas A, Rivera W, Jiménez-García JC (2021) A cascade PID control for a plate-heat-exchanger-based solar absorption cooling system

  • Yuzhong W, Wei M, Hu X, Jiang M, Zhang L (2020) Research on variable universe fuzzy PID control strategy of pipe lining induction heating system. Hindawi modelling and simulation in engineering

  • Zajacs A, Borodiņecs A (2019) Assessment of development scenarios of district heating systems. Sustain Cities Soc 48:101540

    Article  Google Scholar 

  • Zeng D, Zheng Y, Luo W, Hu Y, Cui Q, Li Q, Peng C (2019) Research on improved auto-tuning of a pid controller based on phase angle margin. Energies 12(9):1704

    Article  Google Scholar 

  • Zhang X-M, Han Q-L, Ge X, Ding D, Ding L, Yue D, Peng C (2019) Networked control systems: a survey of trends and techniques. IEEE/CAA J Autom Sin 7(1):1–17

    MathSciNet  Google Scholar 

  • Ziyadanogullari BN, Yucel HL, Yildiz C (2018) Thermal performance enhancement of flat-plate solar collectors by means of three different nanofluids. Therm Sci Eng Progr 8:55–65

    Article  Google Scholar 

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Correspondence to Seema Haribhau Jadhav.

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Jadhav, S.H., Sarwadnya, R.V. Modeling of pine sleek PID control system in AC heat exchanger. J Ambient Intell Human Comput 14, 16159–16171 (2023). https://doi.org/10.1007/s12652-022-03838-5

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