System Identification and Control of a Biotrickling Filter

2015 ◽  
Vol 10 (1) ◽  
pp. 39-53
Author(s):  
Nabil Abdel-Jabbar ◽  
Wasim Ahmed ◽  
Zarook Shareefdeen
Keyword(s):  
Steady State ◽  
Empirical Modeling ◽  
Biotrickling Filter ◽  
Step Response ◽  
Inlet Concentration ◽  
Gas Velocity ◽  
Set Point ◽  
Outlet Concentration ◽  
Rigorous Model ◽  
And Control

Abstract This paper studies empirical modeling and control of a biotrickling filter (BTF) used for air pollution control. Step response transfer function (TF) with first-order-plus-time-delay model and steady-state artificial neural network (NN) model were developed for BTF based on input–output (I/O) data obtained from simulation of a rigorous model. These simple models offer fast predictions compared to the rigorous model and render control implementation for BTF feasible. Gas velocity and inlet concentration of hydrogen sulfide (H2S) (target pollutant) were considered as the main process inputs while outlet concentration of H2S was selected as the BTF performance variable (output). The TF and NN models fitted well with the I/O data and the resulting regression coefficient values were above 0.97. Different simulations with the fitted NN model were performed and compared with the rigorous model data at steady state. The NN model perfectly captured the steady-state behavior of the BTF process. Two control strategies were implemented, namely proportional–integral/feedback control and model predictive control, also known as receding-horizon control. The controllers were based on the fitted TF model representation of BTF under study. For the control structure, gas velocity, inlet concentration, and outlet concentration were selected as manipulated, disturbance and controlled variables, respectively. Through set-point and disturbance change tests, it was observed that the model predictive controller offered superior set-point tracking capabilities while the feedback controller showed better control in dealing with disturbances. However, both controllers provided adequate control in general.

scholarly journals Analisis Penalaan Kontrol PID pada Simulasi Kendali Kecepatan Putaran Motor DC Berbeban menggunakan Metode Heuristik

2013 ◽  
Vol 1 (2) ◽  
pp. 79 ◽  
Author(s):  
WALUYO WALUYO ◽  
ADITYA FITRIANSYAH ◽  
SYAHRIAL SYAHRIAL
Keyword(s):  
Steady State ◽  
Rise Time ◽  
Pid Controller ◽  
Settling Time ◽  
Control Parameters ◽  
Motor Speed ◽  
Set Point ◽  
Dc Motors ◽  
And Control ◽  
Peak Value

ABSTRAKMotor DC banyak digunakan di industri kecil dan besar.Kecepatan motor DC sering tidak stabil akibat gangguan dari luar maupun perubahan parameter dan torsi beban sehingga perlu dilakukan rancangan kontroler.Kontroler yang dirancang menggunakan PID yang terdiri dari tiga jenis cara pengaturan yang dikombinasikan, yaitu kontrol P (Proportional), kontrol I (Integral) dan kontrol D (Derivatif).Kontroler yang dirancang disimulasikan menggunakan perangkat lunak. Hasil simulasi menunjukan kontroler PID untuk kendali kecepatan motor DC ini menghasilkan kondisi robust (kokoh) saat nilai Kp = 1,1, Ti = 0,1, Td = 3,7. Hasil dari parameter kendali yang dirancang memiliki error steady state 0,99 % dan dengan settling time 3,7 detik pada rise time 2,00 detik dan nilai peak terletak pada 0,99. Kecepatan awal yang dihasilkan mendekati set point yang diinginkan pada detik ke 6 dan kecepatannya tidak ada penurunan atau tetap konstan sampai dengan detik ke 100.Kata kunci: Motor DC, PID, Heuristik, Steady State, Rise Time ABSTRACT DC motors are widely used in small and large industries. Their speeds are often unstable due to interference from outside or change the parameters and load torque, so that it was necessary to design a controller. The controller was designed using a PIDconsists of three types of arrangements, which are mutually combined way, namely the control P (Proportional), control I (Integral) and control D (Derivative). The controllers were designed using software for simulation. The simulation results showed the PID controller for DC motor speed control produced robust conditionswhen the value of Kp, Ti and Tdwere 1.1,  0.1 and 3.7 respectively. The results of the control parameters had error steady state 0.99 % and the settling time of 3.7 seconds at 2.0 sec rise time and the peak value was 0,99. The resulted initial velocity was very fast to approach the desired set point in the sixth second and its speed was remain constant until 100thsecond.Keywords: Motor DC, PID, Heuristic, Steady State, Rise Time

Control of an adiabatic continuous reactor by feeding catalyst

1980 ◽  
Vol 45 (11) ◽  
pp. 2903-2918 ◽  
Author(s):  
Josef Horák ◽  
Zina Valášková ◽  
František Jiráček
Keyword(s):  
Steady State ◽  
Reaction Temperature ◽  
Continuous Reactor ◽  
Control Element ◽  
Inlet Temperature ◽  
Switching Cycle ◽  
Point Temperature ◽  
Set Point ◽  
Constant Rate ◽  
Laboratory Reactor

Algorithms have been presented, analyzed and experimentally tested to stabilize the reaction temperature at constant inlet temperature and composition of the feed by controlled dispensing of the catalyst. The information for the control element is the course of the reaction temperature. If the temperature of the reaction mixture is below the set point, the catalyst is being fed into the reactor at a constant rate. If the reaction temperature is higher the catalyst dispenser is blocked; dispensing of the catalyst is not resumed until the set point temperature has been reached again. The amount of catalyst added is a function of the duration of the switching cycle. The effect has been discussed of the form of this function on the course of the switching cycle. The results have been tested experimentally on a laboratory reactor controlled in an unstable steady state.

Reduced substrate oxidation in postischemic myocardium: 13C and 31P NMR analyses

1990 ◽  
Vol 258 (5) ◽  
pp. H1357-H1365 ◽  
Author(s):  
E. D. Lewandowski ◽  
D. L. Johnston
Keyword(s):  
Steady State ◽  
31P Nmr ◽  
Tca Cycle ◽  
High Energy ◽  
Substrate Oxidation ◽  
High Energy Phosphates ◽  
Atp Content ◽  
And Control ◽  
13C And 31P Nmr ◽  
Postischemic Myocardium

13C and 31P nuclear magnetic resonance (NMR) spectra were used to assess substrate oxidation and high-energy phosphates in postischemic (PI) isolated rabbit hearts. Phosphocreatine (PCr) increased in nonischemic controls on switching from glucose perfusion to either 2.5 mM [3-13C]pyruvate (120%, n = 7) or [2-13C]acetate (114%, n = 8, P less than 0.05). ATP content, oxygen consumption (MVO2), and hemodynamics (dP/dt) were not affected by substrate availability in control or PI hearts. dP/dt was 40-60% lower in PI hearts during reperfusion after 10 min ischemia. Hearts reperfused with either pyruvate (n = 11) or acetate (n = 8) regained preischemic PCr levels within 45 s. Steady-state ATP levels were 55-70% of preischemia with pyruvate and 52-60% with acetate. Percent maximum [4-13C]glutamate signal showed reduced conversion of pyruvate to glutamate via the tricarboxylic acid (TCA) cycle at 4-min reperfusion (PI = 24 +/- 4%, means +/- SE; Control = 48 +/- 4%). The increase in 13C signal from the C-4 position of glutamate was similar to control hearts within 10.5 min. The increase in [4-13C]glutamate signal from acetate was not different between PI and control hearts. The ratio of [2-13C]Glu:[4-13C]Glu, reflecting TCA cycle activity, was reduced in PI hearts with acetate for at least 10 min (Control = 0.76 +/- 0.03; PI = 0.51 +/- 0.09) until steady state was reached. Despite rapid recovery of oxidative phosphorylation, contractility remained impaired and substrate oxidation was significantly slowed in postischemic hearts.

scholarly journals A SIMPLE FIVE-STEP METHODOLOGY TO DETERMINE CONTROLLABILITY OF HEAT EXCHANGER NETWORKS USING STEADY-STATE INFORMATION

2011 ◽  
Author(s):  
Rodolfo Tellez ◽  
William Y. Svrcek ◽  
Brent R. Young
Keyword(s):  
Steady State ◽  
Heat Exchanger ◽  
Process Integration ◽  
Plant Design ◽  
State Information ◽  
Step Procedure ◽  
Heat Exchanger Networks ◽  
Propose Control Strategy ◽  
Optimum Heat ◽  
And Control

Process integration design methodologies have been developed and introduced to synthesise an optimum heat exchanger network (HEN) arrangement. However, controllability issues are often overlooked during the early stages of a plant design. In this paper we present a five-step procedure that involves the use of multivariable disturbance and control analyses based solely on steady-state information and with the purpose to assess process design developments and to propose control strategy alternatives appropriate and suitable for a HEN.

Study of Temperature Effect on Servovalve-Controlled Fuel Metering Unit

2015 ◽  
Vol 137 (6) ◽  
Author(s):  
Bin Wang ◽  
Haocen Zhao ◽  
Ling Yu ◽  
Zhifeng Ye
Keyword(s):  
Steady State ◽  
Temperature Variation ◽  
Dynamic Characteristics ◽  
Numerical Study ◽  
Step Response ◽  
Fuel Temperature ◽  
Wide Range ◽  
Fuel Rate ◽  
Testing Condition ◽  
The Given

It is usual that fuel system of an aero-engine operates within a wide range of temperatures. As a result, this can have effect on both the characteristics and precision of fuel metering unit (FMU), even on the performance and safety of the whole engine. This paper provides theoretical analysis of the effect that fluctuation of fuel temperature has on the controllability of FMU and clarifies the drawbacks of the pure mathematical models considering fuel temperature variation for FMU. Taking the electrohydraulic servovalve-controlled FMU as the numerical study, simulation in AMESim is carried out by thermal hydraulic model under the temperatures ranged from −10 to 60 °C to confirm the effectiveness and precision of the model on the basis of steady-state and dynamic characteristics of FMU. Meanwhile, the FMU testing workbench with temperature adjustment device employing the fuel cooler and heater is established to conduct an experiment of the fuel temperature characteristics. Results show that the experiment matches well with the simulation with a relative error no more than 5% and that 0–50 °C fuel temperature variation produces up to 5.2% decrease in fuel rate. In addition, step response increases with the fuel temperature. Fuel temperature has no virtual impact on the steady-state and dynamic characteristics of FMU under the testing condition in this paper, implying that FMU can operate normally in the given temperature range.

scholarly journals Developing the Concepts of Homeostasis, Homeorhesis, Allostasis, Elasticity, Flexibility and Plasticity of Brain Function

NeuroSci ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 372-382
Author(s):  
Alfredo Pereira
Keyword(s):  
Brain Function ◽  
Complex Dynamics ◽  
Stable States ◽  
Set Point ◽  
Brain Functions ◽  
Temporal Phase ◽  
The Central Nervous System ◽  
Elastic Processes ◽  
And Control ◽  
Flexible Processes

I discuss some concepts advanced for the understanding of the complex dynamics of brain functions, and relate them to approaches in affective, cognitive and action neurosciences. These functions involve neuro-glial interactions in a dynamic system that receives sensory signals from the outside of the central nervous system, processes information in frequency, amplitude and phase-modulated electrochemical waves, and control muscles and glands to generate behavioral patterns. The astrocyte network is in charge of controlling global electrochemical homeostasis, and Hodgkin–Huxley dynamics drive the bioelectric homeostasis of single neurons. In elastic processes, perturbations cause instability, but the system returns to the basal equilibrium. In allostatic processes, perturbations elicit a response from the system, reacting to the deviation and driving the system to stable states far from the homeostatic equilibrium. When the system does not return to a fixed point or region of the state space, the process is called homeorhetic, and may present two types of evolution: (a) In flexible processes, there are previously existing “attractor” stable states that may be achieved after the perturbation, depending on context; (b) In plastic processes, the homeostatic set point(s) is(are) changed; the system is in a process of adaptation, in which the allostatic forces do not drive it back to the previous set point, but project to the new one. In the temporal phase from the deviant state to the recovery of stability, the system generates sensations that indicate if the recovery is successful (pleasure-like sensations) or if there is a failure (pain-like sensations).

scholarly journals Investigating the species of microorganisms from activated sludge for handling phenol contaminated-air streams in biotrickling filter

2013 ◽  
Vol 16 (3) ◽  
pp. 96-105
Author(s):  
Anh Thi Kim Nguyen ◽  
Mi Thi Tra Le ◽  
Phu Ly Sy Nguyen ◽  
Nga Diep Yen Dang ◽  
Hien Thi To
Keyword(s):  
Bacillus Thuringiensis ◽  
Activated Sludge ◽  
Removal Efficiency ◽  
High Efficiency ◽  
Bacillus Pumilus ◽  
Air Flow ◽  
Biotrickling Filter ◽  
Inlet Concentration ◽  
Air Streams ◽  
Removal Equipment

This research aimed at investigating the species of microorganisms from activated sludge is capable of handling gas-containing phenol vapor by means of trickling biofilter. By isolating and culturing microorganisms, two species, Bacillus pumilus and Bacillus thuringiensis, was discovered to dominate in phenol vapor removal equipment with high efficiency (about 90% with B. pumilus strain and 92% with B. thuringiensis strains) at inlet concentration about 650 - 850 mg/Nm3 and air flow of 1.5 L/min. Simultaneously, similar experiments were carried out with mixed microorganisms obtained removal efficiency of more than 80%. This result showed that microorganisms after being isolated gave higher performance than mixture of microorganisms. In particular, strain of B. thuringiensis could handle up to 3600 mg/Nm3 in inlet concentration at about 184.3 gphenolm-3.h-1 elimination capacity when removal efficiency was over 92%.

scholarly journals APLIKASI KONTROL PID PADA PROSES PENGOLAHAN AIR LAUT MENGGUNAKAN METODE REVERSE OSMOSIS BERBASIS DCS

JURNAL ELTEK ◽  
2019 ◽  
Vol 17 (2) ◽  
pp. 32
Author(s):  
Hariyadi Singgih Singgih ◽  
Subiyantoro Subiyantoro ◽  
Siswoko Siswoko
Keyword(s):  
Steady State ◽  
Reverse Osmosis ◽  
Rise Time ◽  
Delay Time ◽  
Settling Time ◽  
Set Point ◽  
Pressure Transmitter

Metode pemurnian air laut menggunakan pengaturan kecepatan motor dalam proses reverse osmosis sangat dibutuhkan, dikarenakan proses penyaringan dalam membran reverse osmosis membutuhkan tekanan yang sesuai dengan kemampuan membran. Selain itu juga dibutuhkan kontrol ketinggian air untuk mengotomatisasi tangki yang telah penuh dan mempertahankan ketinggian air. Solusi untuk mengurangi permasalahan ini digunakan DCS yang berfungsi untuk memonitor dan mengontrol plant dari jarak jauh, Metode kontrol yang digunakan pada DCS untuk menstabilkan set point menggunakan metode kontrol PID Ziegler-Nichols. Dalam penelitian ini dirancang mini plant kontrol ketinggian air dan tekanan menggunakan metode PID Ziegler-Nichols yang diimplementasikan pada DCS-PCS7. Sensor yang digunakan untuk ketinggian air adalah HC-SR04, dan untuk sensor tekanan menggunakan pressure transmitter. Dengan aplikasi kontrol PID diperoleh kestabilan set point dengan parameter kontrol ketinggian air : Kp=134.4, Ti=0 dan Td=1. Waktu untuk mencapai set point 120 detik dan  error steady state sebesar 0.94% tanpa gangguan. Untuk parameter Kontrol tekanan air sebesar: Kp=3, Ti=0 dan Td=1.375 dan Delay time = 4s, Rise time = 7s, Settling time = 25s, Osilasi output PID rendah, Error steady state = 1.03% tanpa gangguan.    

scholarly journals Pengkondisian Suhu Air Perebusan Kedelai Pada Pembuatan Tempe Dengan Metode PID

2021 ◽  
Vol 6 (3) ◽  
pp. 40
Author(s):  
Siroju Insan ◽  
Tarmukan Tarmukan ◽  
Mila Fauziyah
Keyword(s):  
Steady State ◽  
Rise Time ◽  
Delay Time ◽  
Set Point

Tempe merupakan makanan tradisional yangpopuler di Indonesia. Salah satu bahan dari tempe adalahkacang kedelai. Cara pembuatannya terdiri dari pengupasan,perebusan, inokulasi, dan peragian. Proses perebusandilakukan dengan merebus kedelai ke dalam air dengan suhutertentu. Tujuan perebusan ialah sebagai proses hidrasi agarkedelai dapat menyerap air sebanyak mungkin. Prosesperebusan yang umum digunakan saat ini masih manualsehingga hasilnya kurang maksimal. Hal ini karena suhu dariproses perebusan secara manual tidak stabil. Oleh karena itu,penelitian ini dilakukan untuk mengontrol suhu pada prosesperebusan agar tetap stabil. Penelitian ini menggunakanmetode kontrol PID untuk mengatur suhu dengan caramengatur besar bukaan valve gas LPG pada tungku. Suhu daritungku dideteksi menggunakan sensor suhu RTD PT100 untukdibandingkan dengan nilai set point. Dengan menggunakanmetode Ziegler-Nichols didapatkan nilai penguatan Kp=50.64,Ki=1.266, dan Kd= 506.4. Dari nilai konstanta Kp, Ki, dan Kdtersebut diperoleh respon output dengan nilai nilaiOvershoot=0.4%, delay time=7.19, rise time=14.38, settlingtime=15.06, error steady-state (atas)=0.67%, dan errorsteady-state (bawah)=1.78%.

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