• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.10-16
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• 2006

In this paper, moving a fragile object from an initial point to a specific location in the minimum time without damage is studied. In order to achieve this goal, initially, the maximum acceleration and velocity ranges are specified. These ranges can be dynamically generate on the planned path by the manipulator. The path can be altered by considering the geometrical constraints. Later, considering the impulsive force constraint on the object, the range of maximum acceleration and velocity are obtained to preserve object safety while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of acceleration and velocity. This time-optimal trajectory planning can be applied to real applications and is suitable for both continuous and discrete paths.

• Smart Structures and Systems
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• v.11 no.6
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• pp.623-635
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• 2013

This paper investigates application of a control algorithm called model predictive sliding mode control (MPSMC) to active vibration suppression of a cantilevered aluminum beam. MPSMC is a relatively new control algorithm where model predictive control is employed to enhance sliding mode control by enforcing the system to reach the sliding surface in an optimal manner. In previous studies, it was shown that MPSMC can be applied to reduce hysteretic effects of piezoelectric actuators in dynamic displacement tracking applications. In the current study, a cantilevered beam with unknown mass distribution is selected as an experimental test bed in order to verify the robustness of MPSMC in active vibration control applications. Experimental results show that MPSMC can reduce vibration of an aluminum cantilevered beam at least by 29% regardless of modified mass distribution.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.355-358
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• 2009

This paper proposes efficiency optimization control of IPMSM drive using multi hybrid fuzzy controller(HFC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on HFC using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using multi HFC. Also, this paper proposes speed control of IPMSM using HFC1, current control of HFC2-HFC3 and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HFC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.9 no.3
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• pp.410-425
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• 1997

Buildings are mostly under part load conditions causing an inefficient system operation in terms of energy consumption. It is critical to operate building air-conditioning system with a scientific or optimal manner which minimizes energy consumption and maintains thermal comfort by matching building sensible and latent loads. Little research has been performed in developing general methodologies for the optimal operation of air-conditioning system. Based on this research motivation, system simulation program was developed by adopting various equipment operating strategies which are energy efficient especially for humidity control in summer. A numerical optimization technique was utilized to search optimal solution for multi-independent variables and then linked to the developed system simulation model within a mam program. The main goal of the study is to provide a systematic framework and guideline for the optimal operation of air-conditioning system focusing on air-side. For given cooling loads and ambient outdoor conditions the optimal operating strategies of a commercial building are determined by minimizing a constrained objective function by a nonlinear programming technique. Desired space setpoint conditions were found through evaluating the trade-offs between comfort and system power consumption. The results show that supply airflow rate and compressor fraction play main roles in the optimization process. It was found that variable setpoint optimization technique could produce lower indoor humidity level demanding less power consumption which will be benefits for building applications of humidity problem.

• Journal of Power Electronics
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• v.19 no.1
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• pp.119-133
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• 2019

Although the dual modulation wave method can solve the low-frequency neutral point potential (NPP) fluctuation problem for three-level neutral point clamped converters, it also increases the switching frequency and limits the zero-sequence voltage. That makes it harmful when dealing with the NPP drift problem if the converter suffers from a long dead time or asymmetric loads. By introducing two degrees of freedom (2-DOF), an NPP control based on a search optimization method can demonstrate its ability to cope with the above mentioned two types of NPP problems. However, the amount of calculations for obtaining an optimal 2-DOF is so large that the method cannot be applied to certain industrial applications with an inexpensive digital signal processor. In this paper, a novel optimal 2-DOF-based NPP control is proposed. The relationships between the NPP and the 2-DOF are analyzed and a method for directly determining the optimal 2-DOF is also discussed. Using a direct calculation method, the amount of calculations is significantly reduced. In addition, the proposed method is able to maintain the strongest control ability for the two types of NPP problems. Finally, some experimental results are given to confirm the validity and feasibility of the proposed method.

• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1823-1833
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• 2006

An immune algorithm is a kind of evolutional computation strategies, which is developed in the basis of a real immune mechanism in the human body. Recently, scientific or engineering applications using this scheme are remarkably increased due to its significant ability in terms of adaptation and robustness for external disturbances. Particularly, this algorithm is efficient to search optimal parameters against complicated dynamic systems with uncertainty and perturbation. In this paper, we investigate an immune algorithm embedded Proportional Integral Derivate (called I-PID) control, in which an optimal parameter vector of the controller is determined offline by using a cell-mediated immune response of the immunized mechanism. For evaluation, we apply the proposed control to mitigation of vibrations for nonlinear structural systems, cased by external environment load such as winds and earthquakes. Comparing to traditional controls under same simulation scenarios, we demonstrate the innovation control is superior especially in robustness aspect.

• Smart Structures and Systems
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• v.30 no.5
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• pp.537-544
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• 2022

The optimal design of structural composite materials is a research topic that attracts the attention of lots researchers. For many more thirty years, there has been increasing interest in the applications in all kinds of topics, which means taking advantage of fuzzy set theory, fuzzy analysis, and fuzzy control for designing high-performance and efficient structural systems is a fundamental concern for engineers, and many applications require the use of a systems approach to combine structural and active control systems. Therefore, an intelligent method can be designed based on the mitigation method, and by establishing the stable of the closed-loop fuzzy mitigation system, the behavior of the closed-loop fuzzy mitigation system can be accurately predicted. In this article, the intelligent algorithm and optimum design of fuzzy theory for structural control has been provided and demonstrated effective and efficient in practical engineering issues.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.123-126
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• 1998

The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. In the Meaning of these foundational concepts, simple genetic algorithm(SGA) allocate more trials to the schemata whose average fitness remains above average. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve in contrast with traditional single population evolutionary algorithms. In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. So we propose a co-evolutionary method finding optimal fuzzy rules. Our algorithm is that after constructing two population groups m de up of rule vase and its schema, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the proposed method to a path planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• Smart Structures and Systems
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• v.24 no.3
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• pp.403-414
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• 2019

Offshore drilling has become a key process for obtaining oil. Offshore platforms have many applications, including oil exploration and production, navigation, ship loading and unloading, and bridge and causeway support. However, vibration problems caused by severe environmental loads, such as ice, wave, wind, and seismic loads, threaten the functionality of platform facilities and the comfort of workers. These concerns may result in piping failures, unsatisfactory equipment reliability, and safety concerns. Therefore, the vibration control of offshore platforms is essential for assuring structural safety, equipment functionality, and human comfort. In this study, an optimal multiple tuned mass damper (MTMD) system was proposed to mitigate the excessive vibration of a three-dimensional offshore platform under ice and earthquake loadings. The MTMD system was designed to control the first few dominant coupled modes. The optimal placement and system parameters of the MTMD are determined based on controlled modal properties. Numerical simulation results show that the proposed MTMD system can effectively reduce the displacement and acceleration responses of the offshore platform, thus improving safety and serviceability. Moreover, this study proposes an optimal design procedure for the MTMD system to determine the optimal location, moving direction, and system parameters of each unit of the tuned mass damper.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.5
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• pp.388-395
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• 2016

Electric vehicles (EV) and hybrid EVs (HEV) are designed and manufactured by GM, Toyota, Honda, and Hyundai motors. The propulsion system design process for EV requires integrating subsystem designs into an overall system model to maximize the performance of a given propulsion architecture. Therefore, high-power density and high-torque density are important attributes required for EV applications. To improve torque and power density, propulsion motors are designed for saturation during high-torque operation. The nonlinearity associated with core saturation is modeled by incorporating the cross-coupling inductances, which also behave nonlinearly. Furthermore, in EV environments, the battery is directly connected to the DC link, and the battery changes depending on the state of charge. It will be onerous if as many optimal current commands as different $V_{dc}$ were made. This paper presents the optimal current commands in the various operating condition and the current control technique in EV environments.