Hybrid Modified Whale Optimisation Algorithm Simulated Annealing Technique for Control of SRM

The evolutionary multiobjective optimization is an identified field for researchers. The goal of evolutionary multiobjective optimization is to optimize several objectives simultaneously. The problem of multiobjective optimisation is more important when the objective function exhibits conflicting characteristics. In this work, metaheuristic techniques such as modified hybrid whale optimization algorithm with simulated annealing (hybrid mWOASA) is proposed for speed control along with minimization of ripple in torque of a 75 KW, 4-phase, 8/6 switched reluctance motor. The proposed method is used for the combined objective of control of speed with minimization of ripple in the output torque of switched reluctance motor (SRM) considering the armature current as constraint. It is noticed that torque ripple coefficient, integral square error of speed (ISE(speed)), and integral square error of current (ISE(current)) reduced significantly by proposed mWOASA technique as compared to hybrid WOASA, WOA.

A novel order reduction method for linear dynamic systems and its application for designing of PID and lead/lag compensators

This paper proposes a new model order reduction technology for the simplification of the complexity of large scale models. The proposed technique is focused on the Mihailov stability approach that guarantees the stability of the reduced model constrained that the complex system is stable. In this scheme, the denominator coefficients of the approximated simplified system are computed by using the Mihailov stability algorithm and the truncation method is used for the determination of coefficients of the numerator polynomial. The effectiveness and efficiency of the proposed approach are illustrated by comparing the step responses of the given system and approximated lower order models. The error indices such as integral square error (ISE), relative integral square error (RISE), integral absolute error (IAE) and integral time weighted absolute error (ITAE) are used as performance indices for comparing the proposed scheme with other existing standard reduced order modeling methods. The obtained reduced model is used for the designing of controllers for the original complex system. A new scheme for the determination of controllers is also proposed for the large scale models with help of reduced order modeling. The proposed technique is validated by applying it to an eighth order flexible-missile control system and a third order fuel control system. The simulation results show the dominance of the proposed methodologies over the latest model diminution techniques available in the literature.

Lion Algorithm with Levy Update: Load frequency controlling scheme for two-area interconnected multi-source power system

In an interconnected multi-area power system, Load Frequency Control (LFC) is a main challenging problem. This paper presents the Fractional Order Proportional Integral (FOPI) controller for an interconnected two-area power system, wherein each area has multi-source power systems. The gains of the proposed controller are being optimized by Lion Algorithm (LA), utilizing an integral square error (ISE) criterion, to develop the proposed Lion with Levy Update-based FOPI controller (LLUFOPI). The proposed LA schedules the gain of the LLUFOPI controller by achieving the least possible error. Hence, the LLUFOPI controller assures better LFC in the two-area interconnected power system. The performance of the proposed controller is assessed by considering the practical constraints in power system such as Generation Rate Constraints (GRC), communication delay, AC/DC link, step load variation and Capacitive Energy Storage (CES) device. Finally, the simulation results show that the LLUFOPI controller provides a well- optimized gain that is 89% higher than the other algorithms with better stability. The Integral Square Error (ISE) value of the proposed controller is 81.1% lesser than the other algorithms. Better LFC in the two-area multi-source-interconnected power system is hence achieved with minimum ISE.

PENGENDALIAN PROSES PURIFIKASI DME DAN METANOL PADA PABRIK DME DARI GAS SINTESIS

Pengembangan produksi DME (dimetil eter) sebagai energi alternatif yang ramah lingkungan sudah banyak dilakukan di negara-negara lain seperti Jerman, Belanda, Australia, Jepang, China dan Taiwan. Indonesia masih mengimpor DME untuk memenuhi seluruh kebutuhan industri dalam negeri, karena itu perlu didirikan pabrik pembuatan DME. Proses pembuatan DME secara indirect melibatkan sintesis metanol, dehidrasi metanol, purifikasi DME hingga purifikasi metanol untuk di recylce. Optimasi proses purifikasi DME dilakukan dengan mendapatkan kinerja pengendalian yang optimum pada proses purifikasi DME hingga purifikasi metanol. Unit-unit yang ada pada proses purifikasi DME ialah unit distilasi DME, unit cooler dan unit storage tank, sedangkan pada proses purifikasi metanol terdapat unit distilasi metanol, unit cooler dan unit pompa. Proses purifikasi DME dan Metanol ini mengandalkan unit distilasi yang memiliki suhu operasi hingga 190oC dan tekanan hingga 1950 kPa. Sistem pengendalian yang dipilih untuk proses ini ialah jenis pengendali Proportional Integral (PI) karena dapat menangani hampir setiap situasi pengendalian proses di dalam skala industri. Penelitian ini menggunakan pemodelan penyetelan pengendali Ziegler Nichols dan Lopez, lalu dibandingkan nilai parameter kinerja pengendalinya yaitu Offset, Rise Time, Time of First Peak, Settling Time, Periode osilasi, Decay Ratio, Overshoot, Deviasi maksimum, Integral Absolute Error (IAE) dan Integral Square Error (ISE) dari kedua jenis penyetelan tersebut. Hasil penelitian ini dapat digunakan untuk penentuan variabel input dan output yang optimum pada proses purifikasi DME dan Metanol yang dapat diterapkan pada pabrik DME.