Pengetahuan Siswa Madrasah Tsanawiyah Muhammadiyah Tawangsari Terhadap Mitigasi Bencana Gempabumi

Mitigasi gempabumi merupakan tindakan yang dilakukan sebelum terjadi bencana gempabumi yang bertujuan untuk mengurangi dampak yang kerusakan yang ditimbulkan baik secara struktural maupun non-struktural. Penelitian Pengetahuan Siswa MTs Muhammadiyah Tawangsari terhadap Mitigasi Bencan Gempabumi bertujuan untuk menghasikan informasi tentang pengetahuan siswa terhadap mitigasi dalam menghadapi bencana gempabumi. Parameter tingkat mitigasi meliputi, pemetaan, pemantauan, penyebaran informasi, sosialisasi dan penyuluhan, pelatihan dan pendidikan, peringatan dini, dan parameter pengetahuan yaitu instrument kegempaan, penyebab gempabumi, dan dampak gempabumi. Metode yang digunakan adalah metode deskriptif kuantitatif dengan menggunakan perhitungan indek dan persentase. Proses analisis data dimulai dengan menelaah data yang tersedia dari berbagai sumber, yaitu observasi, angket, dan dokumentasi. Pengambilan sampel sebanyak 104 siswa sebagai responden dari jumlah populasi 176 siswa MTs Muhammadiyah Tawangasari, dengan melakukan pengujian instrumen penelitian (quisioner) melalui uji vaiditas dan realibiitas. Hasil penelitian menyimpukan sebagai berikut. Pertama tingkat mitigasi siswa MTs Muhammadiyah Tawangsari terhadap bencana gempabumi dikategorikan kuang dengan nilai indeks 33,01. Kedua pengetahuan siswa MTs Muhammadiyah Tawangsari terhadap bencana gempabumi relatif baik karena responden cenderung menjawab sangat setuju dan setuju. Hal tersebut dinilai dari parameter instrument kegempaan dengan persentase sebesar 79,8%, parameter penyebab gempabumi dengan persentase sebesar 54,8%, dan parameter dampak gempabumi dengan persentase sebesar 43,27%

Reaction rate reconstruction from biomass concentration measurement in bioreactors using modified second-order sliding mode algorithms

This paper deals with the estimation of unknown signals in bioreactors using sliding observers. Particular attention is drawn to estimate the specific growth rate of microorganisms from measurement of biomass concentration. In a recent article, notions of high-order sliding modes have been used to derive a growth rate observer for batch processes. In this paper we generalize and refine these preliminary results. We develop a new observer with a different error structure to cope with other types of processes. Furthermore, we show that these observers are equivalent, under coordinate transformations and time scaling, to the classical super-twisting differentiator algorithm, thus inheriting all its distinctive features. The new observers’ family achieves convergence to timevarying unknown signals in finite time, and presents the best attainable estimation error order in the presence of noise. In addition, the observers are robust to modeling and parameter uncertainties since they are based on minimal assumptions on bioprocess dynamics. In addition, they have interesting applications in fault detection and monitoring. The observers performance in batch, fed-batch and continuous bioreactors is assessed by experimental data obtained from the fermentation of Saccharomyces Cerevisiae on glucose.This work was supported by the National University of La Plata (Project 2012-2015), the Agency for the Promotion of Science and Technology ANPCyT (PICT2007-00535) and the National Research Council CONICET (PIP112-200801-01052) of Argentina; the Technical University of Valencia (PAID-02-09), the CICYT (DPI2005-01180) and AECID (A/024186/09) of Spain; and by the project FEDER of the European Union.De Battista, H.; Picó Marco, JA.; Garelli, F.; Navarro Herrero, JL. (2012). Reaction rate reconstruction from biomass concentration measurement in bioreactors using modified second-order sliding mode algorithms. Bioprocess and Biosystems Engineering. 35(9):1-11. https://doi.org/10.1007/s00449-012-0752-yS111359Aborhey S, Williamson D (1978) State amd parameter estimation of microbial growth process. Automatica 14:493–498Bastin G, Dochain D (1986) On-line estimation of microbial specific growth rates. Automatica 22:705–709Bastin G, Dochain D (1990) On-line estimation and adaptive control of bioreactors. Elsevier, AmsterdamBejarano F, Fridman L (2009) Unbounded unknown inputs estimation based on high-order sliding mode differentiator. In: Proceedings of the 48th IEEE conference on decision and control, pp 8393–8398Corless M, Tu J (1998) State and input estimation for a class of uncertain systems. Automatica 34(6):757–764Dabros M, Schler M, Marison I (2010) Simple control of specific growth rate in biotechnological fed-batch processes based on enhanced online measurements of biomass. Bioprocess Biosyst Eng 33:1109–1118Davila A, Moreno J, Fridman L (2010) Variable gains super-twisting algorithm: a lyapunov based design. In: American control conference (ACC), 2010, pp 968–973Dávila J, Fridman L, Levant A (2005) Second-order sliding-mode observer for mechanical systems. IEEE Transact Automatic Control 50(11):1785–1789De Battista H, Picó J, Garelli F, Vignoni A (2011) Specific growth rate estimation in (fed-)batch bioreactors using second-order sliding observers. J Process Control 21:1049–1055Dochain D (2001) Bioprocess control. Wiley, HobokenDochain D (2003) State and parameter estimation in chemical and biochemical processes: a tutorial. J Process Control 13(8):801–818Edwards C, Spurgeon S, Patton R (2000) Sliding mode observers for fault detection and isolation. Automatica 36(2):541–553Evangelista C, Puleston P, Valenciaga F, Fridman L (2012) Lyapunov designed super-twisting sliding mode control for wind energy conversion optimization. Indus Electron IEEE Transact. doi: 10.1109/TIE.2012.2188256Farza M, Busawon K, Hammouri H (1998) Simple nonlinear observers for on-line estimation of kinetic rates in bioreactors. Automatica 34(3):301–318Fridman L, Davila J, Levant A (2008) High-order sliding modes observation. In: International workshop on variable structure systems, pp 203–208Fridman L, Levant A (2002) Sliding mode control in engineering, higher-order sliding modes. Marcel Dekker, Inc., New York, pp 53–101Fridman L, Shtessel Y, Edwards C, Yan X (2008) Higher-order sliding-mode observer for state estimation and input reconstruction in nonlinear systems. Int J Robust Nonlinear Control 18(3–4):399–412Gauthier J, Hammouri H, Othman S (1992) A simple observer for nonlinear systems: applications to bioreactors. IEEE Transact Automatic Control 37(6):875–880Gnoth S, Jenzsch M, Simutis R, Lubbert A (2008) Control of cultivation processes for recombinant protein production: a review. Bioprocess Biosyst Eng 31(1):21–39Hitzmann B, Broxtermann O, Cha Y, Sobieh O, Stärk E, Scheper T (2000) The control of glucose concentration during yeast fed-batch cultivation using a fast measurement complemented by an extended kalman filter. Bioprocess Eng 23(4):337–341Kiviharju K, Salonen K, Moilanen U, Eerikainen T (2008) Biomass measurement online: the performance of in situ measurements and software sensors. J Indus Microbiol Biotechnol 35(7):657–665Levant A (1998) Robust exact differentiation via sliding mode technique. Automatica 34(3):379–384Levant A (2003) Higher-order sliding modes, differentiation and output-feedback control. Int J Control 76(9/10):924–941Lubenova V, Rocha I, Ferreira E (2003) Estimation of multiple biomass growth rates and biomass concentration in a class of bioprocesses. Bioprocess Biosyst Eng 25:395–406Moreno J, Alvarez J, Rocha-Cozatl E, Diaz-Salgado J (2010) Super-twisting observer-based output feedback control of a class of continuous exothermic chemical reactors. In: Proceedings of the 9th IFAC international symposium on dynamics and control of process systems, pp 719–724. Leuven, BelgiumMoreno J, Osorio M (2008) A Lyapunov approach to second-order sliding mode controllers and observers. In: Proceedings of the 47th IEEE conference on decision and control. Cancún, México, pp 2856–2861Moreno J, Osorio M (2012) Strict Lyapunov functions for the super-twisting algorithm. IEEE Transact Automatic Control 57:1035–1040Navarro J, Picó J, Bruno J, Picó-Marco E, Vallés S (2001) On-line method and equipment for detecting, determining the evolution and quantifying a microbial biomass and other substances that absorb light along the spectrum during the development of biotechnological processes. Patent ES20010001757, EP20020751179Neeleman Boxtel (2001) Estimation of specific growth rate from cell density measurements. Bioprocess Biosyst Eng 24(3):179–185November E, van Impe J (2002) The tuning of a model-based estimator for the specific growth rate of Candidautilis. Bioprocess Biosyst Eng 25:1–12Park Y, Stein J (1988) Closed-loop, state and input observer for systems with unknown inputs. Int J Control 48(3):1121–1136Perrier M, de Azevedo SF, Ferreira E, Dochain D (2000) Tuning of observer-based estimators: theory and application to the on-line estimation of kinetic parameters. Control Eng Pract 8:377–388Picó J, De Battista H, Garelli F (2009) Smooth sliding-mode observers for specific growth rate and substrate from biomass measurement. J Process Control 19(8):1314–1323. Special section on hybrid systems: modeling, simulation and optimizationSchenk J, Balaszs K, Jungo C, Urfer J, Wegmann C, Zocchi A, Marison I, von Stockar U (2008) Influence of specific growth rate on specific productivity and glycosylation of a recombinant avidin produced by a Pichia pastoris Mut + strain. Biotecnol Bioeng 99(2):368–377Shtessel Y, Taleb M, Plestan F (2012) A novel adaptive-gain supertwisting sliding mode controller: Methodol Appl Automatica (in press)Soons Z, van Straten G, van der Pol L, van Boxtel A (2008) On line automatic tuning and control for fed-batch cultivation. Bioprocess Biosyst Eng 31(5):453–467Utkin V, Poznyak A, Ordaz P (2011) Adaptive super-twist control with minimal chattering effect. In: Proceedings of 50th IEEE conference on decision and control and European control conference. Orlando, pp 7009–7014Veloso A, Rocha I, Ferreira E (2009) Monitoring of fed-batch E. coli fermentations with software sensors. Bioprocess Biosyst Eng 32(3):381–388Venkateswarlu C (2004) Advances in monitoring and state estimation of bioreactors. J Sci Indus Res 63:491–498Zamboni N, Fendt S, Rühl M, Sauer U (2009) 13c-based metabolic flux analysis. Nat Protocols 4:878–892Zorzetto LFM, Wilson JA (1996) Monitoring bioprocesses using hybrid models and an extended kalman filter. Comput Chem Eng 20(Suppl 1):S689–S69

A procedure for the estimation over time of metabolic fluxes in scenarios where measurements are uncertain and/or insufficient

<p>Abstract</p> <p>Background</p> <p>An indirect approach is usually used to estimate the metabolic fluxes of an organism: couple the available measurements with known biological constraints (e.g. stoichiometry). Typically this estimation is done under a static point of view. Therefore, the fluxes so obtained are only valid while the environmental conditions and the cell state remain stable. However, estimating the evolution over time of the metabolic fluxes is valuable to investigate the dynamic behaviour of an organism and also to monitor industrial processes. Although Metabolic Flux Analysis can be successively applied with this aim, this approach has two drawbacks: i) sometimes it cannot be used because there is a lack of measurable fluxes, and ii) the uncertainty of experimental measurements cannot be considered. The Flux Balance Analysis could be used instead, but the assumption of optimal behaviour of the organism brings other difficulties.</p> <p>Results</p> <p>We propose a procedure to estimate the evolution of the metabolic fluxes that is structured as follows: 1) measure the concentrations of extracellular species and biomass, 2) convert this data to measured fluxes and 3) estimate the non-measured fluxes using the Flux Spectrum Approach, a variant of Metabolic Flux Analysis that overcomes the difficulties mentioned above without assuming optimal behaviour. We apply the procedure to a real problem taken from the literature: estimate the metabolic fluxes during a cultivation of CHO cells in batch mode. We show that it provides a reliable and rich estimation of the non-measured fluxes, thanks to considering measurements uncertainty and reversibility constraints. We also demonstrate that this procedure can estimate the non-measured fluxes even when there is a lack of measurable species. In addition, it offers a new method to deal with inconsistency.</p> <p>Conclusion</p> <p>This work introduces a procedure to estimate time-varying metabolic fluxes that copes with the insufficiency of measured species and with its intrinsic uncertainty. The procedure can be used as an off-line analysis of previously collected data, providing an insight into the dynamic behaviour of the organism. It can be also profitable to the on-line monitoring of a running process, mitigating the traditional lack of reliable on-line sensors in industrial environments.</p

Model Dinamika Sistem Dalam Optimalisasi Biaya Distribusi Pupuk Domestik (Wilayah Tanggung Jawab PT Pupuk Iskandar Muda)

Industri pupuk di Indonesia memiliki peluang pasar yang cukup besar, hingga menarik pesaing baru dari negara-negara asing. Meskipun kapasitas produksi domestik dari perusahaan-perusahaan milik negara cukup untuk memenuhi permintaan, impor pupuk masih cukup besar. Hal ini menimbulkan opportunity cost bagi produsen lokal yang harus bersaing dengan perusahaan asing yang menawarkan harga kompetitif. PT Pupuk Iskandar Muda (PIM) merupakan salah satu perusahaan dalam industri pupuk dengan wilayah tanggung jawab yang meliputi Sumatra Barat, Sumatra Utara, Riau – Kep. Riau, dan Aceh, menghadapi tantangan dalam mendistribusikan pupuk secara efektif untuk memenuhi kebutuhan konsumen dan menjaga stok minimum. Untuk menjawab tantangan tersebut, studi ini mengembangkan scenario distribusi alternatif dengan mempertimbangkan efisiensi biaya, keandalan pasokan, lokasi, waktu, dan faktor transportasi. Skenario-skenario tersebut melibatkan distribusi multimoda dengan dua moda transportasi, menggunakan kapal untuk gudang level II dan truk untuk gudang level III. Empat skenario distribusi utama diformulasikan, termasuk perjalanan general cargo single trip dan milk run, serta perjalanan container single trip dan milk run. Skenario truck terdiri dari in bag truk dan containerized in bag truk. Simulasi dilakukan dengan menggunakan metode System dynamics untuk menggambarkan, memodelkan, mensimulasikan, dan menganalisis masalah atau sistem yang kompleks secara dinamis, dan dengan menggunakan software Powersim Studio 8 untuk mengevaluasi tingkat persediaan, biaya distribusi, dan dampak fluktuasi konsumsi pupuk. Kebijakan yang optimal dan model optimasi, serta penyesuaian jumlah perjalanan kapal dan tingkat transfer diperlukan untuk dapat mempertahankan minimum stock dan memastikan pasokan pupuk yang dapat diandalkan. Dari hasil simulasi diketahui bahwa pada cluster Sumatra Utara dan Riau – Kepri, biaya distribusi terendah didapatkan dengan menggunakan scenario container single trip dengan kapasitas kapal 167 TEUs. Sedangkan pada cluster Sumatra Barat sendiri, biaya terendah didapatkan dengan menggunakan scenario general cargo milk run dengan kapasitas kapal 7.175-ton. Untuk cluster Aceh sendiri dengan model distribusi all-truck, scenario in bag trucking merupakan skenario dengan biaya terendah. Biaya distribusi bergantung pada komponen biaya yang digunakan dalam model, sehingga penggunaan input yang efektif dalam sistem distribusi mampu memberikan biaya yang efektif pula. =============================================================================================================================== The fertiliser industry in Indonesia has considerable market opportunities, attracting new competitors from foreign countries. Although the domestic production capacity of state-owned companies is sufficient to meet demand, fertiliser imports are still substantial. This creates opportunity costs for local producers who must compete with foreign companies that offer competitive prices. PT Pupuk Iskandar Muda (PIM), one of the companies in the fertiliser industry with an area of responsibility covering West Sumatra, North Sumatra, Riau - Riau Islands, and Aceh, faces the challenge of distributing fertiliser effectively to meet consumer needs and maintain minimum stocks. To address these challenges, this study develops alternative distribution scenarios by considering cost efficiency, supply reliability, location, timing, and transport factors. The scenarios involve multimodal distribution with two modes of transport, using ships for level II warehouses and trucks for level III warehouses. Four main distribution scenarios were formulated, including general cargo single trip and milk run, and container single trip and milk run. The truck scenario consists of in bag trucks and containerised in bag trucks. Simulations were conducted using the System dynamics method to dynamically describe, model, simulate, and analyse complex problems or systems, and using Powersim Studio 8 software to evaluate inventory levels, distribution costs, and the impact of fluctuations in fertiliser consumption. Optimal policies and optimisation models, as well as adjustments to the number of ship trips and transfer rates are required to be able to maintain minimum stock and ensure reliable fertiliser supply. From the simulation results, it is known that in the North Sumatra and Riau - Riau Islands clusters, the lowest distribution cost is obtained by using a single trip container scenario with a ship capacity of 167 TEUs. While in the West Sumatra cluster itself, the lowest cost is obtained by using the general cargo milk run scenario with a ship capacity of 7,175-tonnes. For the Aceh cluster itself with the all-truck distribution model, the in bag trucking scenario is the lowest cost scenario. Distribution costs depend on the cost components used in the model, so the use of effective inputs in the distribution system can provide effective costs as well

Nonlinear observers for locally uniformly observable systems

This paper deals with the observability analysis and the observer synthesis of a class of nonlinear systems. In the single output case, it is known [4-6] that systems which are observable independently of the inputs, admit an observable canonical form. These systems are called uniformly observable systems. Moreover, a high gain observer for these systems can be designed on the basis of this canonical form. In this paper, we extend the above results to multi-output uniformly observable systems. Corresponding canonical forms are presented and sufficient conditions which permit the design of constant and high gain observers for these systems are given

Extended high gain observer design

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Observer design with mixed continuous and multirate sampled outputs involving multiple time-varying delays

International audienc

A simple filtered high gain observer for a class of uncertain nonlinear systems

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Discrete-time observer for a class of nonlinear systems

A discrete-time observer for a class of nonlinear systems is proposed in this paper. The proposed observer is a direct forward Euler discretization of the continuous-time observer given in [6] for uniformly observable systems. An extension of the observer design to a larger class of systems is also given

On-line estimation of the reaction rates in bioreactors from multirate sampled outputs with multiple delays

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