• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1195-1198
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• 1993

We investigate a systematic design procedure of automated rule generation of fuzzy logic based controller for uncertain dynamic systems such as an engine dynamic model.“Automated Tuning”means autonomous clustering or collection of such meaningful transitional relations in the state-space. Optimal control strategies are included in the design procedures, such as minimum squared error, minimum time, minimum energy or combined performance criteria. Fuzzy feedback control systems designed by the cell-state transition method have the properties of closed-loop stability, robustness under parameter variabtions, and a certain degree of optimality. Most of all, the main advantage of the proposed approach is that reliability can be potentially increased even if a large grain of uncertainty is involved within the control system under consideration. A numerical example is shown in which we apply our strategic fuzzy controller design to a highly nonlinear model of engine idle speed contr l.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.109-117
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• 2022

This paper proposes a method for detecting flight anomalies of drones through the difference between the command of flight controller (FC) and the navigation solution. If the drones make a flight normally, control errors generated by the difference between the desired control command of FC and the navigation solution should converge to zero. However, there is a risk of sudden change or divergence of control errors when the FC control feedback loop preset for the normal flight encounters interferences such as strong winds or navigation sensor abnormalities. In this paper, we propose the method with a deep neural network model that predicts the control error in the normal flight so that the abnormal flight state can be detected. The performance of proposed method was evaluated using the real-world flight data. The results showed that the method effectively detects anomalies in various situation.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.659-665
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• 2000

In this paper a platoon merging control system is considered as a remotely located system with state represented by a stochastic process. in the system it is common to encounter situations where a single decision maker controls a large number of subsystems and observation and control signals are sent over a communication channel with finite capacity and significant transmission delays. Unlike a classical estimation problem where the observation is a continuous process corrupted by additive noise there is a constraint that the observation must be coded and transmitted over a digital communication channel with fintie capacity. A recursive coder-estimator sequence is a state estimation scheme based on observations transmitted with finite communication capacity constraint. in this paper we introduce a stochastic model for the lead vehicle in a platoon of vehicles in a lane considering the angle between the road surface and a horizontal plane as a stochastic process. In order to merge two platoons the lead vehicle of the following platoon is controlled by a remote control station. Using the observation transmitted over communication channel the remote control station designs the feedback controller. The simulation results show that the intervehicle spacings and the deviations from the desired intervehicle spacing are well regulated.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.963-968
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• 1990

An iterative learning control scheme for tracking control of a class of uncertain nonlinear systems is presented. By introducing a model reference adaptive controller in the learning control structure, it is possible to achieve zero tracking of unknown system even when the upperbound of uncertainty in system dynamics is not known apriori. The adaptive controller pull the state of the system to the state of reference model via control gain adaptation at each iteration, while the learning controller attracts the model state to the desired one by synthesizing a suitable control input along with iteration numbers. In the controller role transition from the adaptive to the learning controller takes place in gradually as learning proceeds. Another feature of this control scheme is that robustness to bounded input disturbances is guaranteed by the linear controller in the feedback loop of the learning control scheme. In addition, since the proposed controller does not require any knowledge of the dynamic parameters of the system, it is flexible under uncertain environments. With these facts, computational easiness makes the learning scheme more feasible. Computer simulation results for the dynamic control of a two-axis robot manipulator shows a good performance of the scheme in relatively high speed operation of trajectory tracking.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.729-733
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• 1987

Stability of Co Semigroups perturbed via the steady state Riccati equation (SSRE) is studied. We consider an infinite dimensional system : .chi. over dot = A.chi. + Bu, in, (A), domain of A, where A is the infinitesimal generator of a Co semigroup [T(t), t.geq.0] in H. If the original Co semigroup [T(t), t.geq.0] has a lower bound : vertical bar T(t).chi. vertical bar .geq. k vertical bar .chi. vertical bar, for all .chi. in H. t.geq. 0 and k>0, then the perturbed Co semigroup via the SSRE, where the feedback operator B is compact, cannot be exponentially stable. Physical interpretation of this result is as follows : in real applications, a finite number of actuators are available, therefore the operator B is compact. When the original system is inherently unstable, that is, has an infinite number of unstable modes, the perturbed system via the SSRE cannot be stable with a uniform decay rate.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.3-75
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• 2001

This paper addresses the design of State-feedback Robust Guaranteed-Cost Controllers with controller gain variations. Since the unstructured uncertainty is the most dominant uncertainty in the modeling of the plant, the plant is assumed to have the unstructured uncertainty. It is necessary to take the controller parameter perturbation into consideration when we design the robust controller. Otherwise, the resulting controller may show the fragility property. That is to say, the extremely small controller parameter variation may result in the instability of the overall closed-loop system. Therefore, the design purpose is that the maximum performance index is guaranteed in the presence of the unstructured plant uncertainty and controller parameter variations ...

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.344-348
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• 1992

This paper describes a procedure to design a hovering flight controller for a model helicopter using LQG theory. Parameters of the model helicopter in hover are obtained using direct measurements and calculations proposed by other research. A feedback co is by using digital LQG theory. First, a full state feedback controller is designed to the discretized system taking desirable transient response and other assumptions into account. Then a full-state estimator is designed and revised until desirable response is obtained while global stability is maintained. Performance of the controller is tested by computer simulations. Experiments have been performed using a 3-degree-of-freedom gimbal that holds the model helicopter, and the controller exhibited stable hover capability.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.398-403
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• 1998

This paper describes a controller design for the stator reactive power generator in the transmission system. The controller of static reactive power generator was designed using a mathematical model and non-linear state feedback. The performance of controller was verified using computer simulation with EMTP code and experimental work with scaled-model. The dynamic interaction with a simple power system was also analyzed using both the simulation model and hardware scaled-model. Both simulation and experimental results prove that the controller using PI block and non-linear state feedback offers better performance than the controller using PI block only.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.58-62
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• 1998

In the industrial motor drive systems, a torsional vibration is often generated because of the elastic elements in torque transmission. One of general methods for the system is H$\infty$ controller to suppress the torsional vibration and reject the torque disturbance. vibration and reject the torque disturbance. Moreover, the two-degrees-of-freedom controller, which includes the H$\infty$ controller, is designed in order to improve the command following property. In this paper, we propose a new H$\infty$ controller with partial state feedback. This method having simple structure satisfies with the fast command following property and the attenuation of disturbances and vibrations simultaneously, just like the complicated TDOF H$\infty$ controller

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.496-508
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• 1999

Fuzzy System which are based on membership functions and rules can control nonlinear uncertain complex systems well. However Fuzzy logic controller(FLC) has problems; It is difficult to design the stable FLC and FLC depends mainly on individual experience. Although FLC can be designed using the error back-propagation algorithm it takes long time to converge into global optimal parameters. Well-developed linear system theory should not be replaced by FLC but instead it should be suitably used with FLC. A new methodology is introduced for designing THEN-PART membership functions of FLC based on its well-tuned state feedback controller. A example of inverted pendulum is given for demonstration of the robustness of proposed methodology.