scholarly journals Multiobjective Optimal Control of FOPID Controller for Hydraulic Turbine Governing Systems Based on Reinforced Multiobjective Harris Hawks Optimization Coupling with Hybrid Strategies

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Wenlong Fu ◽  
QiPeng Lu
Keyword(s):  
Latin Hypercube Sampling ◽  
Hydraulic Turbine ◽  
Parameter Tuning ◽  
Absolute Error ◽  
Operating Conditions ◽  
Test Problems ◽  
Operation Conditions ◽  
Load Disturbance ◽  
Multiobjective Optimal Control ◽  
Fractional Order Pid

The controlling parameter tuning of the hydraulic turbine governing system (HTGS) is always deduced under single operating condition and is not suitable for the changeable operating conditions of the hydraulic turbine. For this purpose, multiobjective optimization problem of fractional order PID (FOPID) controller for HTGS is constructed through the consideration of no-load disturbance and on-load disturbance operation conditions, where the performance indicators of integral time absolute error (ITAE) under both operation conditions are employed as the objective functions. To achieve the optimum, the multiobjective version of newly proposed Harris hawks optimization (MOHHO) is established to solve the optimization issue. Additionally, hybrid strategies which include Latin hypercube sampling initialization, modified differential evolution operator, and mutation operator are coupled into MOHHO (HMOHHO) to promote the global searching capability. Simultaneously, the linear model of rabbit energy within MOHHO is replaced with a nonlinear one to further enhance the searching capacity. Subsequently, the effectiveness and superiority of the proposed HMOHHO are verified by several multiobjective UF and ZDT test problems. Finally, the practical application and contrastive analysis ascertain that the constructed multiobjective problem of FOPID controller is suitable for HTGS under changeable operating conditions, and the proposed HMOHHO is effective in solving the issue.

scholarly journals Multiobjective Optimization of a Fractional-Order PID Controller for Pumped Turbine Governing System Using an Improved NSGA-III Algorithm under Multiworking Conditions

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Chu Zhang ◽  
Tian Peng ◽  
Chaoshun Li ◽  
Wenlong Fu ◽  
Xin Xia ◽  
...  
Keyword(s):  
Fractional Order ◽  
Working Conditions ◽  
Chaos Theory ◽  
Latin Hypercube Sampling ◽  
Absolute Error ◽  
Initial Population ◽  
Latin Hypercube ◽  
Governing System ◽  
Pumped Storage ◽  
Fractional Order Pid

In order to make the pump turbine governing system (PTGS) adaptable to the change of working conditions and suppress the frequency oscillation caused by the “S” characteristic area running at middle or low working water heads, the traditional single-objective optimization for fractional-order PID (FOPID) controller under single working conditions is extended to a multiobjective framework in this study. To establish the multiobjective FOPID controller optimization (MO-FOPID) problem under multiworking conditions, the integral of the time multiplied absolute error (ITAE) index of PTGS running at low and high working water heads is adopted as objective functions. An improved nondominated sorting genetic algorithm III based on Latin hypercube sampling and chaos theory (LCNSGA-III) is proposed to solve the optimization problem. The Latin hypercube sampling is adopted to generate well-distributed initial population and take full of the feasible domain while the chaos theory is introduced to enhance the global search and local exploration ability of the NSGA-III algorithm. The experimental results on eight test functions and a real-world PTGS have shown that the proposed multiobjective framework can improve the Pumped storage units’ adaptability to changeable working conditions and the proposed LCNSGA-III algorithm is able to solve the MO-FOPID problem effectively.

scholarly journals Multiobjective Optimal Control for Hydraulic Turbine Governing System Based on an Improved MOGWO Algorithm

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Xin Xia ◽  
Jie Ji ◽  
Chao-shun Li ◽  
Xiaoming Xue ◽  
Xiaolu Wang ◽  
...  
Keyword(s):  
Optimal Control ◽  
Hydraulic Turbine ◽  
Power Grids ◽  
Grey Wolf Optimizer ◽  
Test Problems ◽  
Operation Condition ◽  
Operation Conditions ◽  
Multiobjective Problems ◽  
Governing System ◽  
Multiple Operation

Hydraulic turbine governing system (HTGS) is essential equipment which regulates frequency and power of the power grids. In previous studies, optimal control of HTGS is always aiming at one single operation condition. The variation of operation conditions of HTGS is seldom considered. In this paper, multiobjective optimal function is proposed for HTGS under multiple operation conditions. In order to optimize the solution to the multiobjective problems, a novel multiobjective grey wolf optimizer algorithm with searching factor (sMOGWO) is also proposed with two improvements: adding searching step to search more no-domain solutions nearby the wolves and adjusting control parameters to keep exploration ability in later period. At first, the searching ability of the sMOGWO has been verified on several UF test problems by statistical analysis. And then, the sMOGWO is applied to optimize the solutions of the multiobjective problems of HTGS, while different algorithms are employed for comparison. The experimental results indicate that the sMOGWO is more effective algorithm and improves the control quality of the HTGS under multiple operation conditions.

Design of an environmentally friendly fuel based on a synthetic composite nano-catalyst through parameter estimation and process modeling

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Aysar T. Jarullah ◽  
Sarmad K. Muhammed ◽  
Ban A. Al-Tabbakh ◽  
Iqbal M. Mujtaba
Keyword(s):  
Process Modeling ◽  
Batch Reactor ◽  
Optimization Technique ◽  
Oxidative Desulfurization ◽  
Environmentally Friendly ◽  
Absolute Error ◽  
Operating Conditions ◽  
Operation Conditions ◽  
Nano Catalyst ◽  
Light Gas Oil

Abstract In this paper, oxidative desulfurization (ODS) process is studied for the purpose of removing the sulfur components from light gas oil (LGO) via experimentation and process modeling. A recently developed (by the authors) copper and nickel oxide based composite nano-catalyst is used in the process. The ODS experiments are conducted in a batch reactor and air is used as an oxidizer under moderate operation conditions. Determination of the kinetic parameters with high accuracy is necessary of the related chemical reactions to develop a helpful model for the ODS operation giving a perfect design of the reactor and process with high confidence. High conversion of 92% LGO was obtained under a reaction temperature of 413 K and reaction time of 90 min for synthesized Cu Ni /HY nano-catalyst. Here model based optimization technique incorporating experimental data is used to estimate such parameters. Two approaches (linear and non-linear) are utilized to estimate the best kinematic parameters with an absolute error of less than 5% between the predicted and the experimental results. An environmentally friendly fuel is regarded the main goal of this study, therefore the optimization process is then employed utilizing the validated model of the prepared composite nano-catalyst to get the optimal operating conditions achieving maximum conversion of such process. The results show that the process is effective in removing more than 99% of the sulfur from the LGO resulting in a cleaner fuel.

scholarly journals A Tamper-Resistant Algorithm Using Blockchain for the Digital Tachograph

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 581
Author(s):  
Yongbae Kim ◽  
Juyong Back ◽  
Jongweon Kim
Keyword(s):  
Wireless Communication ◽  
Statistical Tests ◽  
Operating Conditions ◽  
External Memory ◽  
Data Recording ◽  
Storage Devices ◽  
Suggested Algorithm ◽  
Operation Conditions ◽  
Before And After ◽  
Verification Test

A tachograph in a vehicle records the vehicle operating conditions, such as speed, distance, brake operation conditions, acceleration, GPS information, etc., in intervals of one second. For accidents, the tachograph records information, such as the acceleration and direction of a vehicle traveling in intervals of 1/100 s for 10 s before and after the accident occurs as collision data. A vehicle equipped with a tachograph is obliged to upload operation data to administrative organizations periodically via other auxiliary storage devices like a USB attached external memory or online wireless communication. If there is a problem with the recorded contents, data may be at risk of being tampered with during the uploading process. This research proposed tamper-resistant technology based on blockchain for data in online and offline environments. The suggested algorithm proposed a new data recording mechanism that operates in low-level hardware of digital tachographs for tamper-resistance in light blockchains and on/offline situations. The average encoding time of the proposed light blockchain was 1.85 ms/Mb, while the average decoding time was 1.65 ms/Mb. With the outliers in statistical tests removed, the estimated average encoding and decoding time was 1.32 ms/Mb and 1.29 ms/Mb, respectively, and the tamper verification test detected all the tampered data.

scholarly journals Modeling of a Real-Life Industrial Reactor for Hydrogenation of Benzene Process

Catalysts ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 412
Author(s):  
Mirosław K. Szukiewicz ◽  
Krzysztof Kaczmarski
Keyword(s):  
Catalyst Activity ◽  
Real Life ◽  
Operating Conditions ◽  
Reactor Operation ◽  
Reactor Model ◽  
High Scale ◽  
Industrial Reactor ◽  
Knowledge Based ◽  
Operation Conditions ◽  
Insight Into

A dynamic model of the hydrogenation of benzene to cyclohexane reaction in a real-life industrial reactor is elaborated. Transformations of the model leading to satisfactory results are presented and discussed. Operating conditions accepted in the simulations are identical to those observed in the chemical plant. Under those conditions, some components of the reaction mixture vanish, and the diffusion coefficients of the components vary along the reactor (they are strongly concentration-dependent). We came up with a final reactor model predicting with reasonable accuracy the reaction mixture’s outlet composition and temperature profile throughout the process. Additionally, the model enables the anticipation of catalyst activity and the remaining deactivated catalyst lifetime. Conclusions concerning reactor operation conditions resulting from the simulations are presented as well. Since the model provides deep insight into the process of simulating, it allows us to make knowledge-based decisions. It should be pointed out that improvements in the process run, related to operating conditions, or catalyst application, or both on account of the high scale of the process and its expected growth, will remarkably influence both the profits and environmental protection.

Measurement of Unsteady Flow in Pump-Turbine for Hydropower Using PIV Method

2009 ◽  
Author(s):  
Nobuhiko Fukuda ◽  
Satoshi Someya ◽  
Koji Okamoto
Keyword(s):  
Rotational Speed ◽  
Velocity Measurement ◽  
Numerical Procedure ◽  
Hydraulic Turbine ◽  
Operating Conditions ◽  
High Time ◽  
Pump Turbine ◽  
Guide Vanes ◽  
Runner Blade ◽  
Wide Range

It is thought that the pressure fluctuation can occur due to the interaction between flow through guide vanes and flow into runner blades, resulting in a vibration of turbine and a blade cracking, in a hydraulic turbine operated in a wide range for flexible power demand. High accurate velocity measurement with high time/spatial resolution can help to clarify the mechanism of the interaction and to provide good experimental data for the validation of numerical procedure. So the aim of present study is to estimate the unstable velocity field quantitatively in the area between guide vanes and runner blades, using high time-resolved particle image velocimetry (PIV). Two types of velocity measurements were carried out, i.e., phase-locked measurement and high time sequential velocity measurement, in a pump-turbine model with 20 guide vanes and 6 runner blades. The characteristic of the flow field varied corresponding to the operating conditions such as flow rate and rotational speed. Opening angles of guide vanes were kept uniform. A clockwise vortex was generated at inside of the runner blade under smaller rotational speed. A counterclockwise vortex was separated at the backside of the runner blade under higher rotational speed. At any operating conditions, the velocity between guide vanes and runner blades oscillated periodically at the blade passing frequency.

scholarly journals Alginate/porous silica matrices for the encapsulation of living organisms: tunable properties for biosensors, modular bioreactors, and bioremediation devices

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Mercedes Perullini ◽  
Mariano Calcabrini ◽  
Matías Jobbágy ◽  
Sara A. Bilmes
Keyword(s):  
Physical Stability ◽  
Porous Silica ◽  
Biological Response ◽  
Optical Quality ◽  
Operating Conditions ◽  
Radius Of Gyration ◽  
Host Matrix ◽  
Operation Conditions ◽  
Step Procedure ◽  
Living Organisms

Abstract:The encapsulation of living cells within inorganic silica hydrogels is a promising strategy for the design of biosensors, modular bioreactors, and bioremediation devices, among other interesting applications, attracting scientific and technological interest. These hostguest multifunctional materials (HGFM) combine synergistically specific biologic functions of their guest with those of the host matrix enhancing their performance. Although inorganic immobilization hosts present several advantages over their (bio)polymer-based counterparts in terms of chemical and physical stability, the direct contact of cells with silica precursors during synthesis and the constraints imposed by the inorganic host during operating conditions have proved to influence their biological response. Recently, we proposed an alternative two-step procedure including a pre-encapsulation in biocompatible polymers such as alginates in order to confer protection to the biological guest during the inorganic and more cytotoxic synthesis. By means of this procedure, whole cultures of microorganisms remain confined in small liquid volumes generated inside the inorganic host, providing near conventional liquid culture conditions.Moreover, the fact of protecting the biological guest during the synthesis of the host, allows extending the synthesis parameters beyond biocompatible conditions, tuning the microstructure of the matrix. In turn, the microstructure (porosity at the nanoscale, radius of gyration of particles composing the structure, and fractal dimension of particle clusters) is determinant of macroscopic parameters, such as optical quality and transport properties that govern the encapsulation material’s performance. Here, we review the most interesting applications of the two-step procedure, making special emphasis on the optimization of optical, transport and mechanical properties of the host as well as in the interaction with the guest during operation conditions.

Artificial Neural Networks Used As a Rule Selector for Fuzzy Logic Controllers

1993 ◽  
Author(s):  
Shou-Heng Huang ◽  
Ron M. Nelson
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Absolute Error ◽  
Operating Conditions ◽  
Delta Rule ◽  
Rule Sets ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Set Up ◽  
And Control

Abstract A feedforward, three-layer, partially-connected artificial neural network (ANN) is proposed to be used as a rule selector for a rule-based fuzzy logic controller. This will allow the controller to adapt to various control modes and operating conditions for different plants. A principal advantage of an ANN over a look up table is that the ANN can make good estimates to fill in for missing data. The control modes, operating conditions, and control rule sets are encoded into binary numbers as the inputs and outputs for the ANN. The General Delta Rule is used in the backpropagation learning process to update the ANN weights. The proposed ANN has a simple topological structure and results in a simple analysis and relatively easy implementation. The average square error and the maximal absolute error are used to judge if the correct connections between neurons are set up. Computer simulations are used to demonstrate the effectiveness of this ANN as a rule selector.

PSO and GA tuned conventional and fractional order PID controllers for quadrotor control

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hasan Saribas ◽  
Sinem Kahvecioglu
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Controller Design ◽  
Optimization Problems ◽  
Parameter Tuning ◽  
Absolute Error ◽  
Cost Functions ◽  
Pid Controllers ◽  
Content Type ◽  
Quadrotor Control

Purpose This study aims to compare the performance of the conventional and fractional order proportional-integral-derivative (PID and FOPID) controllers tuned with a particle swarm optimization (PSO) and genetic algorithm (GA) for quadrotor control. Design/methodology/approach In this study, the gains of the controllers were tuned using PSO and GA, which are included in the heuristic optimization methods. The tuning processes of the controller’s gains were formulated as optimization problems. While generating the objective functions (cost functions), four different decision criteria were considered separately: integrated summation error (ISE), integrated absolute error, integrated time absolute error and integrated time summation error (ITSE). Findings According to the simulation results and comparison tables that were created, FOPID controllers tuned with PSO performed better performances than PID controllers. In addition, the ITSE criterion returned better results in control of all axes except for altitude control when compared to the other cost functions. In the control of altitude with the PID controller, the ISE criterion showed better performance. Originality/value While a conventional PID controller has three parameters (Kp, Ki, Kd) that need to be tuned, FOPID controllers have two additional parameters (µ). The inclusion of these two extra parameters means more flexibility in the controller design but much more complexity for parameter tuning. This study reveals the potential and effectiveness of PSO and GA in tuning the controller despite the increased number of parameters and complexity.

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