• Smart Structures and Systems
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• v.31 no.3
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• Steel and Composite Structures
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• v.47 no.4
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• pp.513-521
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• 2023

The goal of this work is to create a new and improved GWO (Grey Wolf Optimizer), the so-called Robot GWO (RGWO), for dynamic and static target tracking involving multiple robots in unknown environmental conditions. From applying ourselves with the Gray Wolf Optimization Algorithm (GWO) and how it works, as the name suggests, it is a nature-inspired metaheuristic based on the behavior of wolf packs. Like other nature-inspired metaheuristics such as genetic algorithms and firefly algorithms, we explore the search space to find the optimal solution. The results also show that the improved optimal control method can provide superior power characteristics even when operating conditions and design parameters are changed.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.563-573
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• 2007

Optimal design of an automotive catalytic converter for minimization of cold-start emissions is numerically performed using a micro genetic algorithm for two optimization problems: optimal geometry design of the monolith for various operating conditions and optimal axial catalyst distribution. The optimal design process considered in this study consists of three modules: analysis, optimization, and control. The analysis module is used to evaluate the objective functions with a one-dimensional single channel model and the Romberg integration method. It obtains new design variables from the control module, produces the CO cumulative emissions and the integral value of a catalyst distribution function over the monolith volume, and provides objective function values to the control module. The optimal design variables for minimizing the objective functions are determined by the optimization module using a micro genetic algorithm. The control module manages the optimal design process that mainly takes place in both the analysis and optimization modules.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.674-682
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• 2017

This paper presents an optimal initial firing angle control based on the energy consumption and regenerative energy of a parallel multi-pulse thyristor dual converter for urban railway power substations. To prevent short circuiting the thyristor dual converter, a hysteresis band for maintaining a zero-current discontinuous section (ZCDS) is essential during mode changes. During conversion from the ZCDS to forward or reverse mode, the DC trolley voltage can be stabilized by selecting the optimal initial firing angle without an overshoot and slow response. However, the optimal initial firing angle is different depending on the line impedance of each converter. Therefore, the control algorithm for tracking the optimal initial firing angle is proposed to eliminate the overshoot and slow response of DC trolley voltage. Simulations and experiments show that the proposed algorithm yields the fastest DC voltage control performance in the transient state by tracking the optimal firing angle.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.4
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• pp.77-83
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• 1994

In this paper, an optimal control of first order systems is discussed. The control system comprises a main controller and an auxiliary controller. The main controller is designed based on the LQ control scheme including an integrator to remove the off-set. The non-linear auxiliary controller is added parallely to the main controller to obtain a finite time settling control. The control parameters under variation of the system and various coefficients of the performance indices are computed numerically, and the control responses for the system with the proposed controllers demonstrated the usefulness of the control method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.790-798
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• 2011

An efficient sequential computation algorithm of kinematic optimal control is suggested for redundancy resolution of freefloating manipulators. Utilization of minimum principle usually requires involved and tedious procedure of differentiation of Hamiltonian. Due to the constraints of momentum conservation, it is not easy to get exact differential equations of boundary value problem for even relatively simple free-floating manipulator models. To overcome this difficulty, we developed an effective sequential algorithm for the computation of terms appeared in the differential equations. The usefulness of suggested approach is verified by simulation of a planar 3-joints free-floating manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2309-2312
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• 2003

This paper presents the minimization of the energy costs based on energy saving for industrial retort process of canned food. The approved proposed method is related the optimal steam or hot water flow control to achieve desired temperature of retort process. The smooth response and zero steady state error can be also achieved. The performances of the proposed control technique were observed using a small tuna canned food plant in Thailand as an illustrative example. The experimental results are given to support the saving in energy costs and some benefits of the proposed technique.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2319-2324
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• 2003

This paper addresses the optimal design of dividing wall distillation column which is rapidly applied in a variety of chemical processes over recent several years because of its high energy saving efficiency. A general dividing wall column model which can cope with the heat transfer through the dividing wall is developed using rigorous computer simulation. Based on the simulation model, the effects of the internal recycle flow distribution around the dividing wall and the heat transfer across the dividing wall on overall system performance are investigated. An improved method is suggested to utilize the heat transfer through the wall to optimal column design. The suggested method is compared with the existing method via. simulation study and shows more improved energy saving result. Several control strategies for the divided wall column are tested and the optimal control strategy is propose

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.596-606
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• 2008

In this paper, we present a co-design methodology of dynamic optimal network-bandwidth allocation (ONBA) and adaptive control for networked control systems (NCSs) to optimize overall control performance and reduce total network-bandwidth usage. The proposed dynamic co-design strategy integrates adaptive feedback control with real-time scheduling. As part of this co-design methodology, a "closed-loop" ONBA algorithm for NCSs with communication constraints is presented. Network-bandwidth is dynamically assigned to each control loop according to the quality of performance (QoP) information of each control loop. As another part of the co-design methodology, a network quality of service (QoS)-adaptive control design approach is also presented. The idea is based on calculating new control values with reference to the network QoS parameters such as time delays and packet losses measured online. Simulation results show that this co-design approach significantly improves overall control performance and utilizes less bandwidth compared to static strategies.

• Journal of the Korean Mathematical Society
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• v.50 no.1
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• pp.173-187
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• 2013

This paper studies the properties of solutions of the Riccati equation arising from the quadratic optimal control problem of the general damped second order system. Using the semigroup theory, we establish the weak differential characterization of the Riccati equation for a general class of the second order distributed systems with arbitrary damping terms.