• Journal of Power System Engineering
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• v.13 no.6
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• pp.43-50
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• 2009

If an internal combustion engine is operated by consolidated control, the minimum fuel consumption is achieved satisfying the demanded objectives. For this, it is necessary that the engine is operated on the ideal operating line which satisfies minimum fuel consumption. In this context of view, there are many tries to achieve given object. However, the parameter in the internal combustion engines are variable and depend on the operating points. Therefore, it is necessary to cope with the uncertainties such that the optimal operating may be possible. From this point of view, this paper gives a controller design method and a robust stability condition for engine torque control which satisfies the given control performance and robust stability in the presence of physical parameter perturbation. Exactly, the present paper considers a robust stability of this 2DOF servosystem with nonlinear type uncertainty in the engine system, and a robust stability condition for the servosystem is introduced. This result guarantees that if the plant uncertainty is in the permissible set defined by the given condition then a gain tuning can be carried out to suppress the influence of the plant uncertainties.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.4
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• pp.305-316
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• 2014

As avionics and mechanical devices have been developed, the size of unmanned aerial vehicle (UAV) is getting smaller. However, the complicated and accurate missions are provided to the UAV. Among various types of UAVs, quadrotors are widely used for their availability by virtue of simple structure and hovering function. However, the control of quadrotor is highly constrained, because the quadrotor is an under-actuated system which has only 4 actuator inputs. To deal with this under-actuated problem, a new quadrotor model with two more actuators in addition to the 4 propeller inputs is provided to make the system fully-actuated. For the proposed model, a controller is designed using feedback linearization methods. To validate the model and to verify the performance of the proposed controller, numerical simulation is performed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.339-345
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• 2000

This paper deals with the displacement estimation of magnetically suspended simple 1 DOF(degree of freedom) system without the displacement sensor. Inherently electro-magnet for control has two natural feedback loops. One is the transfer function which represents the dependance of the amount of the magnetic flux on the gap displace-ments. The other is the transfer function expressing the properties that the back electromotive force is derived from the time derivative of the magnetic flux. Through these two feedback loops, information about the gap length can be represented by the magnetic flux and the coil current. This means that the gap length can be detected from these two states variables of the electromagnet without a displacements sensor(self-sensing). The displacement can be estimated with the magnetic flux subtracted by the coil current. In this paper we use a balance beam in order to deal with the displacement sensorless estimation of the magnetic bearing system. For the stable estimation of the gap displacements by using the method of self-sensing simple PD controller is used. We first show the mathematical model of the balance beam, and then we show the effectiveness of the current and flux feedback for making stable estimation of the gap displacements for the balance beam. Simulation results show the effectiveness of the current and flux feedback for good estimation of the displacement without using displacement sensor.

• Structural Engineering and Mechanics
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• v.38 no.1
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• pp.39-63
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• 2011

Referring to the formulation of physical stochastic optimal control of structures and the scheme of optimal polynomial control, a nonlinear stochastic optimal control strategy is developed for a class of structural systems with hysteretic behaviors in the present paper. This control strategy provides an amenable approach to the classical stochastic optimal control strategies, bypasses the dilemma involved in It$\hat{o}$-type stochastic differential equations and is applicable to the dynamical systems driven by practical non-stationary and non-white random excitations, such as earthquake ground motions, strong winds and sea waves. The newly developed generalized optimal control policy is integrated in the nonlinear stochastic optimal control scheme so as to logically distribute the controllers and design their parameters associated with control gains. For illustrative purposes, the stochastic optimal controls of two base-excited multi-degree-of-freedom structural systems with hysteretic behavior in Clough bilinear model and Bouc-Wen differential model, respectively, are investigated. Numerical results reveal that a linear control with the 1st-order controller suffices even for the hysteretic structural systems when a control criterion in exceedance probability performance function for designing the weighting matrices is employed. This is practically meaningful due to the nonlinear controllers which may be associated with dynamical instabilities being saved. It is also noted that using the generalized optimal control policy, the maximum control effectiveness with the few number of control devices can be achieved, allowing for a desirable structural performance. It is remarked, meanwhile, that the response process and energy-dissipation behavior of the hysteretic structures are controlled to a certain extent.

• Ocean Systems Engineering
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• v.6 no.3
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• pp.265-287
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• 2016

The change of the global performance of a turret-moored FPSO (Floating Production Storage Offloading) with DP (Dynamic Positioning) control is simulated, analyzed, and compared for two different internal turret location cases; bow and midship. Both collinear and non-collinear 100-yr GOM (Gulf of Mexico) storm environments and three cases (mooring-only, with DP position control, with DP position+heading control) are considered. The horizontal trajectory, 6DOF (degree of freedom) motions, fairlead mooring and riser tension, and fuel consumptions are compared. The PID (Proportional-Integral-Derivative) controller based on LQR (linear quadratic regulator) theory and the thrust-allocation algorithm which is based on the penalty optimization theory are implemented in the fully-coupled time-domain hull-mooring-riser-DP simulation program. Both in collinear and non-collinear 100-yr WWC (wind-wave-current) environments, the advantage of mid-ship turret is demonstrated by the significant reduction in heave at the turret location due to the minimal coupling with pitch mode, which is beneficial to mooring and riser design. However, in the non-collinear WWC environment, the mid-turret case exhibits unfavorable weathervaning characteristics, which can be reduced by employing DP position and heading controls as demonstrated in the present case studies. The present study also reveals the plausible cause of the failure of mid-turret Gryphon Alpha FPSO in milder environment than its survival condition.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.