• Title/Summary/Keyword: Optimal Control Technology

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A Study on the Adaptive Roll Control Scheme for the Top Attack Smart Projectile (상부공격 지능탄의 회전각 적응제어 기법 연구)

  • 홍종태;정수경;최상경
    • Journal of the Korea Institute of Military Science and Technology
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    • v.3 no.2
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    • pp.61-70
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    • 2000
  • An Adaptive Positive Position Feedback method is presented for controlling the roll of the supersonic smart projectile. The proposed strategy combines the attractive attributes of Positive Position Feedback(PPF) of Goh and Caughey, and Lyapunov stability theorem. The parameters of Adaptive-PFF controller are adjusted in an adaptive mauler in order to follow the performance of an optimal reference model. In this way, optimal damping and zero steady-state errors can be achieved even in the presence of uncertain or changing plant parameters. The performance obtained with the Adaptive-PPF algorithm is compared with conventional PPF control algorithm. The results obtained emphasize the potential of Adaptive-PPF algorithm as an efficient means for controlling plants such as supersonic flight systems with uncertainties in real time.

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A Comprehensive Survey of Optimal Placement and Coordinated Control Techniques of FACTS Controllers in Multi-Machine Power System Environments

  • Singh, Bindeshwar;Sharma, N.K.;Tiwari, A.N.
    • Journal of Electrical Engineering and Technology
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    • v.5 no.1
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    • pp.79-102
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    • 2010
  • This paper presents exhaustive review of various methods/techniques for coordinated control between FACTS controllers in multi-machine power systems. It also reviews various techniques/methods for optimal choice and allocation of FACTS controllers. Authors strongly believe that this survey article will be very much useful to the researchers for finding out the relevant references in the field of placement and coordination of FACTS Controllers.

Computational Method of Fuel Optimal Control in Regulator System

  • Lee, Bong-Jin
    • Nuclear Engineering and Technology
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    • v.1 no.2
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    • pp.79-85
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    • 1969
  • Determination of a two-point boundary value problem is the key of finding the control function u(f) with the application of the fundamental idea of Minimum principle. The late development shows the discovery of the initial testate vector for the solution of a two-point value problem. As a new technique of determining the optimal control function, Newton's sequential method is examined in this paper.

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Application of machine learning in optimized distribution of dampers for structural vibration control

  • Li, Luyu;Zhao, Xuemeng
    • Earthquakes and Structures
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    • v.16 no.6
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    • pp.679-690
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    • 2019
  • This paper presents machine learning methods using Support Vector Machine (SVM) and Multilayer Perceptron (MLP) to analyze optimal damper distribution for structural vibration control. Regarding different building structures, a genetic algorithm based optimization method is used to determine optimal damper distributions that are further used as training samples. The structural features, the objective function, the number of dampers, etc. are used as input features, and the distribution of dampers is taken as an output result. In the case of a few number of damper distributions, multi-class prediction can be performed using SVM and MLP respectively. Moreover, MLP can be used for regression prediction in the case where the distribution scheme is uncountable. After suitable post-processing, good results can be obtained. Numerical results show that the proposed method can obtain the optimized damper distributions for different structures under different objective functions, which achieves better control effect than the traditional uniform distribution and greatly improves the optimization efficiency.

Strategy based PSO for Dynamic Control of UPFC to Enhance Power System Security

  • Mahdad, Belkacem;Bouktir, T.;Srairi, K.
    • Journal of Electrical Engineering and Technology
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    • v.4 no.3
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    • pp.315-322
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    • 2009
  • Penetration and installation of a new dynamic technology known as Flexible AC Transmission Systems (FACTS) in a practical and dynamic network requires and force expert engineer to develop robust and flexible strategy for planning and control. Unified Power Flow Controller (UPFC) is one of the recent and effective FACTS devices designed for multi control operation to enhance the power system security. This paper presents a dynamic strategy based on Particle Swarm Optimization (PSO) for optimal parameters setting of UPFC to enhance the system loadability. Firstly, we perform a multi power flow analysis with load incrementation to construct a global database to determine the initial efficient bounds associated to active power and reactive power target vector. Secondly a PSO technique applied to search the new parameters setting of the UPFC within the initial new active power and reactive power target bounds. The proposed approach is implemented with Matlab program and verified with IEEE 30-Bus test network. The results show that the proposed approach can converge to the near optimum solution with accuracy, and confirm that flexible multi-control of this device coordinated with efficient location enhance the system security of power system by eliminating the overloaded lines and the bus voltage violation.

Fuzzy-Sliding Mode Control of a Polishing Robot Based on Genetic Algorithm

  • Go, Seok-Jo;Lee, Min-Cheol;Park, Min-Kyu
    • Journal of Mechanical Science and Technology
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    • v.15 no.5
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    • pp.580-591
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    • 2001
  • This paper proposes a fuzzy-sliding mode control which is designed by a self tuning fuzzy inference method based on a genetic algorithm. Using the method, the number of inference rules and the shape of the membership functions of the proposed fuzzy-sliding mode control are optimized without the aid of an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. It is further guaranteed that the selected solution becomes the global optimal solution by optimizing Akaikes information criterion expressing the quality of the inference rules. In order to evaluate the learning performance of the proposed fuzzy-sliding mode control based on a genetic algorithm, a trajectory tracking simulation of the polishing robot is carried out. Simulation results show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the trajectory control result is similar to the result of the fuzzy-sliding mode control which is selected through trial error by an expert. Therefore, a designer who does not have expert knowledge of robot systems can design the fuzzy-sliding mode controller using the proposed self tuning fuzzy inference method based on the genetic algorithm.

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Framework for End-to-End Optimal Traffic Control Law Based on Overlay Mesh

  • Liu, Chunyu;Xu, Ke
    • Journal of Communications and Networks
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    • v.9 no.4
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    • pp.428-437
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    • 2007
  • Along with the development of network, more and more functions and services are required by users, while traditional network fails to support all of them. Although overlay is a good solution to some demands, using them in an efficient, scalable way is still a problem. This paper puts forward a framework on how to construct an efficient, scalable overlay mesh in real network. Main differences between other overlays and ours are that our overlay mesh processes some nice features including class-of-service(CoS) and traffic engineering(TE). It embeds the end-to-end optimal traffic control law which can distribute traffic in an optimal way. Then, an example is given for better understanding the framework. Particularly, besides good scalability, and failure recovery, it possesses other characteristics such as routing simplicity, self-organization, etc. In such an overlay mesh, an applicable source routing scheme called hierarchical source routing is used to transmit data packet based on UDP protocol. Finally, a guideline derived from a number of simulations is proposed on how to set various parameters in this overlay mesh, which makes the overlay more efficient.

A Study on Performance Enhancement for Remote Operation of Industrial Equipments

  • Lho, Tae-Jung;Joo, Hyun-Woo;Kang, Dong-Jung;Song, Se-Hoon;Park, Ki-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.813-817
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    • 2003
  • By increasing trades between countries, importance of harbors is becoming serious, including our country. When it comes to Container Crane Operation, the most important matter is how many containers are loaded in a truck or a ship by given time. This can be a crucial matter of harbors in taking care of materials. The present harbors' crane uses a wire-rope conveyance materials are transported in the air and have high free-angle of location. The sway can cause the delay of time, wrong position of Trolley and the damage of materials. In this study, we obtain the optimal PID parameters with GA(Genetic Algorithm) and apply those parameters to the PID Controller. In the result of the experimentation, we can see how effectively the PID controller, applied with the optimal parameters obtained by GA, can control the sway angle.

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Optimal Control Design for Automatic Ship Berthing by Using Bow and Stern Thrusters

  • Bui, Van Phuoc;Jeong, Jeong-Soon;Kim, Young-Bok;Kim, Dong-Wook
    • Journal of Ocean Engineering and Technology
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    • v.24 no.2
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    • pp.10-17
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    • 2010
  • Conventionally, because it is difficult to control a ship in shallow water and because attempting to do so creates unwanted environmental effects, maneuvering ships in the harbor area for berthing is usually done with the assistance of tugboats. In this paper, we propose a new method for berthing ships automatically by using bow and stern thrusters. Specifically, a steering motion model of a ship is considered, and parameters in the equation are evaluated by the system identification technique. An optimal controller based on observations was designed from the linearization of the non-linear ship motion in the horizontal plane. It is used to reduce the uncertainty about the ship's dynamics and reduce measurement requirements. The performance of the controller was also analyzed for its robustness relative to avoiding disturbing the environment due to winds, currents, and wave-drift forces. Experiments were conducted to estimate the potential for identifying result and the design of the controller. Specifically, in this paper, the system modeling and tracking control approach are discussed based on a two-degree-of-freedom (2DOF) servo-system design.

Semi-active control of smart building-MR damper systems using novel TSK-Inv and max-min algorithms

  • Askari, Mohsen;Li, Jianchun;Samali, Bijan
    • Smart Structures and Systems
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    • v.18 no.5
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    • pp.1005-1028
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    • 2016
  • Two novel semi-active control methods for a seismically excited nonlinear benchmark building equipped with magnetorheological dampers are presented and evaluated in this paper. While a primary controller is designed to estimate the optimal control force of a magnetorheological (MR) damper, the required voltage input for the damper to produce such desired control force is achieved using two different methods. The first technique uses an optimal compact Takagi-Sugeno-Kang (TSK) fuzzy inverse model of MR damper to predict the required voltage to actuate the MR dampers (TSKFInv). The other voltage regulator introduced here works based on the maximum and minimum capacities of MR damper at each time-step (MaxMin). Both semi-active algorithms developed here, use acceleration feedback only. The results demonstrate that both TSKFInv and MaxMin algorithms are quite effective in seismic response reduction for wide range of motions from moderate to severe seismic events, compared with the passive systems and performs better than original and Modified clipped optimal controller systems, known as COC and MCOC.