• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.460-467
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• 2018

Metaheuristic optimization approach has become the new framework for control synthesis. The main purposes of the control design are command (input) tracking and load (disturbance) regulating. This article proposes an optimal proportional-integral-derivative (PID) controller design for the DC motor speed control system with tracking and regulating constrained optimization by using the cuckoo search (CS), one of the most efficient population-based metaheuristic optimization techniques. The sum-squared error between the referent input and the controlled output is set as the objective function to be minimized. The rise time, the maximum overshoot, settling time and steady-state error are set as inequality constraints for tracking purpose, while the regulating time and the maximum overshoot of load regulation are set as inequality constraints for regulating purpose. Results obtained by the CS will be compared with those obtained by the conventional design method named Ziegler-Nichols (Z-N) tuning rules. From simulation results, it was found that the Z-N provides an impractical PID controller with very high gains, whereas the CS gives an optimal PID controller for DC motor speed control system satisfying the preset tracking and regulating constraints. In addition, the simulation results are confirmed by the experimental ones from the DC motor speed control system developed by analog technology.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.1
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• pp.31-40
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• 2023

Recent advances in flash technologies, such as 3D processing and multileveling schemes, have successfully increased the flash capacity. Unfortunately, these technology advances significantly degrade flash's reliability due to a smaller cell geometry and a finer-grained cell state control. In this paper, we propose an asymmetric BER-aware reliability optimization technique (aBARO), new flash optimization that improves the flash reliability. To this end, we first reveal that bit errors of 3D NAND flash memory are highly skewed among flash cell states. The proposed aBARO exploits the unique per-state error model in flash cell states by selecting the most error-prone flash states and by forming narrow threshold voltage distributions (for the selected states only). Furthermore, aBARO is applied only when the program time (tPROG) gets shorter when a flash cell becomes aging, thereby keeping the program latency of storage systems unchanged. Our experimental results with real 3D MLC and TLC flash devices show that aBARO can effectively improve flash reliability by mitigating a significant number of bit errors. In addition, aBARO can also reduce the read latency by 40%, on average, by suppressing the read retries.

• Geomechanics and Engineering
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• v.32 no.3
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• pp.271-291
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• 2023

Settlement estimation in cohesion materials is a crucial topic to tackle because of the complexity of the cohesion soil texture, which could be solved roughly by substituted solutions. The goal of this research was to implement recently developed machine learning features as effective methods to predict settlement (S_m) of shallow foundations over cohesion soil properties. These models include hybridized support vector regression (SVR), random forests (RF), and coot optimization algorithm (COM), and black widow optimization algorithm (BWOA). The results indicate that all created systems accurately simulated the S_m, with an R² of better than 0.979 and 0.9765 for the train and test data phases, respectively. This indicates extraordinary efficiency and a good correlation between the experimental and simulated S_m. The model's results outperformed those of ANFIS - PSO, and COM - RF findings were much outstanding to those of the literature. By analyzing established designs utilizing different analysis aspects, such as various error criteria, Taylor diagrams, uncertainty analyses, and error distribution, it was feasible to arrive at the final result that the recommended COM - RF was the outperformed approach in the forecasting process of S_m of shallow foundation, while other techniques were also reliable.

• Structural Engineering and Mechanics
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• v.84 no.4
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• pp.489-502
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• 2022

This paper is aimed at developing an optimization-based Finite Element model updating approach for structural damage identification and quantification. A modal flexibility-based error function is introduced, which uses modal assurance criterion to formulate the updating problem as an optimization problem. Because of the inexplicit input/output relationship between the candidate solutions and the error function's output, a robust and efficient optimization algorithm should be employed to evaluate the solution domain and find the global extremum with high speed and accuracy. This paper proposes a new multi-stage Selective Particle Swarm Optimization (SPSO) algorithm to solve the optimization problem. The proposed multi-stage strategy not only fixes the premature convergence of the original Particle Swarm Optimization (PSO) algorithm, but also increases the speed of the search stage and reduces the corresponding computational costs, without changing or adding extra terms to the algorithm's formulation. Solving the introduced objective function with the proposed multi-stage SPSO leads to a smart feedback-wise and self-adjusting damage detection method, which can effectively assess the health of the structural systems. The performance and precision of the proposed method are verified and benchmarked against the original PSO and some of its most popular variants, including SPSO, DPSO, APSO, and MSPSO. For this purpose, two numerical examples of complex civil engineering structures under different damage patterns are studied. Comparative studies are also carried out to evaluate the performance of the proposed method in the presence of measurement errors. Moreover, the robustness and accuracy of the method are validated by assessing the health of a six-story shear-type building structure tested on a shake table. The obtained results introduced the proposed method as an effective and robust damage detection method even if the first few vibration modes are utilized to form the objective function.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.240-245
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• 1990

A on-line optimization scheme based on model in a binary distillation process is proposed. A reduced-order model utilized the concept of collocation is used as a process model and the recursive prediction error method is employed to identify the reduced-order model. The concentrations of end products are controlled by nonlinear adaptive predictive control algorithm. The objective function is constructed to find optimum operate condition for saving utility cost. The proposed optimization is scheme is tested through simulation studies in 13-staged water-methanol distillation column.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11B
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• pp.961-967
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• 2008

Congestion control is one of major mechanisms to avoid dropped packets. Many researchers use optimization theories to find an efficient way to reduce congestion in networks, but they do not consider robustness that may lead to unstable network utilities. This paper proposes a new methodology in order to solve a congestion control problem for wired networks by using a robust design principle. In our particular numerical example, the proposed method provides robust solutions that guarantee high and stable network utilities.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1994.11a
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• pp.146-149
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• 1994

A nonlinear dynamic optimization has been performed for reactor power control system of CANDU 6 nuclear power plant considering xenon, fuel and moderator temperature feedback effects. Integral-of-Time-multiplied Absolute-Error (ITAE) criterion has been used as a performance index of the system behavior. Optimum controller gain are found by searching algorithm of Sequential Quadratic Programming (SQP). System models are referenced from most recent literatures. Signal flow network construction and optimization have been done by using commercial computer software package.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.1131-1132
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• 2011

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.405-423
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• 2022

The distance vector-hop (DV-Hop) is one of the emblematic algorithms that use node connectivity for locating, which often accompanies by a large positioning error. To reduce positioning error, the bio-inspired algorithm and weight optimization model are introduced to address positioning. Most scholars argue that the weight value decreases as the hop counts increases. However, this point of view ignores the intrinsic relationship between the error and weight. To address this issue, this paper constructs the relationship model between error and hop counts based on actual communication characteristics of sensor nodes in wireless sensor network. Additionally, we prove that the error converges to 1/6CR when the hop count increase and tendency to infinity. Finally, this paper presents a modified error-oriented weight positioning model, and implements it with genetic algorithm. The experimental results demonstrate excellent robustness and error removal.

• Journal of Aerospace System Engineering
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• v.15 no.5
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• pp.8-15
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• 2021

This paper describes a design method using an optimization technique to satisfy the longitudinal handling quality of high maneuverable jet aircraft. The dynamic inversion technique was applied to the target aircraft, and the control gain optimization satisfied the longitudinal short-period handling quality, however, the stability margin was not considered. If the stability margin is not satisfied, it is necessary to directly readjust the gains through trial and error methods for improvement. To improve this, an additional compensator and an optimization constraint were added to the control gain optimization procedure. In addition, the degree of handling quality satisfaction with the optimization result was reevaluated, and additional control evaluation criteria for the convergence of the time response and the steady state error that the flight performance requirement set as the optimization constraint cannot be reflected, and the results are described.