• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2624-2626
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• 2000

The stabilization controls of coupled tank system and ball-beam system are difficult control tasks because of their high order time delay, nonlinearity and structural unstability. Fuhermore, a series of classical methods such as a conventional PID and a full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. Therefore, in this paper, in order to stabilize two representative nonlinear system mentioned above, a Sliding Mode Controller based on a Real Variable Elitist Genetic Algorithm(RVEGA SMC) was proposed.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2348-2351
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• 2000

In order to operate SI(Spark Ignition) engine at the optimal fuel efficiency, it is necessary to use continuously variable transmission(CVT) which has more excellent fuel consumption property than transmissions of gear box types commonly used. This study introduces new type of nonlinear control approach to control precisely CVT including nonlinear characteristics. The nonlinear controller is basically composed of input-state feedback linearization, which can cancel the nonlinearities included in CVT on specific controllable area, and sliding-mode control. In this paper, good control performance of contrtol system with the nonlinear controller is confirmed with computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.315-322
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• 2004

A direct adaptive state-feedback controller for highly nonlinear systems is proposed. This paper considers uncertain or ill-defined nonaffine nonlinear systems and employs a static fuzzy logic system (FLS). The employed FLS estimates. and adaptively cancels an unknown plant nonlinearity using its proved universal approximation property. A control law and adaptive laws for unknown fuzzy parameters and bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov. The tracking error is guaranteed to be uniformly asymptotically stable rather than uniformly ultimately bounded with the aid of an additional robustifying control term. No a priori knowledge of an upper bound on an lumped uncertainty is required.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1131-1133
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• 1996

In this paper, we consider the mixed $L_1/H_{\infty}$ problems of finding internally stabilizing controllers which minimize the peak-to-peak gain of a certain closed loop transfer function with $H_{\infty}$-norm constraint on other closed loop transfer function(or vise versa). This problem is a useful framework for designing a controller with the norm constraints upon time and frequency domain. We formulate the mixed $L_1/H_{\infty}$ problem as LMI problems by using the reachable set. This paper offers the sufficient condition for the existence of suboptimal state feedback controller, and shows that suboptimal solution can be obtained by solving a finite-dimensional convex optimization and a line search.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.293-295
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• 1993

Most control system design problems involve finding state feedback gain for good response by the pole or characteristic polynomial assignment. In this paper, the characteristic polynomial assignment using PID controller for discrete 2-dimensional system descrived by the Fornasini-Marchesini's 2nd model (F-MM II) is considered. This method it not only available to F-MM II but also to Rosser's model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.402-408
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• 2017

This paper deals with a robust ${\mathfrak{H}}_{\infty}$ controller design problem for waypoints tracking of large displacement unmanned underwater vehicles (LDUUVs) in Takagi-Sugeno fuzzy form. The LDUUV model uses a rudder to control its horizontal motion. We determine the order of waypoints based on their priorities and consider only surge force. A fuzzy controller in state-feedback form is taken and its design condition of is represented in terms of linear matrix inequalities. A numerical simulation is included to show the effectiveness of the theoretical development.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.580-583
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• 2003

The general time optimal control law provides the optimal solution for a minimum time control problem. But in most real systems with disturbances and model uncertainties, the time optimal control law leads to chattering effect. This chattering effect can cause the system to be unstable. Therefore, we propose a robust optimal control algorithm for the nonlinear second order systems with model uncertainty. The proposed algorithm is combined with bang-bang control and sliding mode control. Thus the proposed algorithm has two state space regions to implement to control algorithm. In each region, the appropriate linear or nonlinear feedback control law is used satisfying the dynamic system equations. Simulation results show the superiority of the proposed controller in comparison with pure time optimal control(bang-bang control).

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.10
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• pp.947-959
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• 2001

We propose a control scheme to control the indoor zone temperature via variable air volume (VAV) unit. To control the room temperature, state space model of the conditioned zone which is partitioned into nine artificial sectional regions is derived. The nonlinearity of the damper motion and actuator are considered for the practical use in the state space system description. The temperature control of the room temperature is performed by manipulating the degree of openness of the damper in relation to the local room temperature and the supplied air flow rate. In general, since a local temperature in the conditioned zone is measured, it is required to estimate the temperature values in each regions for the precise temperature control. We thus design a state observer to estimate the regional temperature, and use these values in the controller. The overall control system consists of the state observer based state feedback with the integral control. We compared the control results of the proposed scheme with those of cascade proportional and integral (PI) control, and showed that the scheme achieved precise control of the conditioned system.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.159-169
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• 2004

In this study, integration control of air-cell seat and semi-active suspension is proposed to minimize the road-tyre force which can cause uncomfortable feeling to rider. The proposed integration control with sliding perturbation observer is consisted of air-cell seat control which uses the force generated by air-cell and the sky-hook control. The air-cell seat itself has been modeled as a 1 degree of freedom spring-damper system. The actual characteristics of the air-cell have been analyzed through experiments. In this paper, we introduces a new robust motion control algorithm using partial state feedback for a nonlinear system with modelling uncertainties and external disturbances. The major contribution of this work is the development and design of robust observer for the state and the perturbation. The combination skyhook controller and air-cell controller using the observer improves control performance, because of the robust routine called Sliding Observer Design for Integration Control of Air-Cell Seat and Semi-active Suspension. The simulation results show a high accuracy and a good performance.

• Journal of Power Electronics
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• v.11 no.5
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• pp.719-725
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• 2011

This paper describes a novel Direct Torque Control (DTC) method for adjustable speed Doubly-Fed Induction Machine (DFIM) drives which is supplied by a two-level Space Vector Modulation (SVM) voltage source inverter (DTC-SVM) in the rotor circuit. The inverter reference voltage vector is obtained by using input-output feedback linearization control and a DFIM model in the stator a-b axes reference frame with stator currents and rotor fluxes as state variables. Moreover, to make this nonlinear controller stable and robust to most varying electrical parameter uncertainties, a two layer recurrent Artificial Neural Network (ANN) is used to estimate a certain function which shows the machine lumped uncertainty. The overall system stability is proved by the Lyapunov theorem. It is shown that the torque and flux tracking errors as well as the updated weights of the ANN are uniformly ultimately bounded. Finally, effectiveness of the proposed control approach is shown by computer simulation results.