Wookyong Kwon

Event-triggered proportional-derivative control for nonlinear network systems with a novel event-triggering scheme: Differential of triggered state consideration

This article proposes event-triggered proportional-derivative control for a class of nonlinear network control systems. For derivative action of the proposed proportional-derivative control, a novel event-triggering scheme is devised together with the control that considers a differential of a triggered state. The class of the nonlinear network systems is represented as a Lur’e system to consider various nonlinear cases. Time varying transmission delay is considered which can be defined by lower and upper delay bounds. The proposed proportional-derivative control is designed by Lyapunov–Krasovskii stability analysis, and the design condition is presented by linear matrix inequalities. The proposed event-triggered proportional-derivative control and event-triggering condition are verified with numerical simulation.

Active vibration control of a strip in a continuous galvanizing line using PI λ D μ -type fractional-order PID controller

In this paper, PIλDμ-type fractional-order proportional-integral-derivative (FOPID) used electromagnetic strip vibration control is proposed for a continuous galvanizing line (CGL). Since a FOPID controller has two more extra tuning knobs than conventional PID controller, FOPID gives more flexibility for the design of a control system, and has better opportunity to adjust system dynamics. FOPID control parameters are found by particle swarm optimization (PSO) that simulated with a finite element method (FEM) model, which was extracted from pilot tester through three-dimensional FEM package ANSYS. Simulation results show that strip oscillation and strip transient response time can be significantly reduced when using proposed PIλDμ-type FOPID controller.

Robust H 2 filter design for bilinear systems using T-S fuzzy approach

In this paper, the H2 filtering of bilinear systems is considered using T-S fuzzy approach. For the bounded input, the bilinear system can be transformed to the Takagi-Sugeno (T-S) fuzzy dynamic system by putting the control input as the premise variable. Then the robust H2 filter for T-S fuzzy system is designed upon existing results using the linear matrix inequality(LMI). The feasibility and effectiveness of the designed filter is shown in the numerical example section.

Development of HILS Simulator for Steering Control in Hot Strip Finishing Mill

In this paper, hardware-in-the loop-simulation(HILS) simulator for steering control is developed. The simulator describes lateral movement of the strip in hot strip finishing mill. The simulator include strip dynamics, mill model, mill motor and AGC controllers. The factors considered for strip dynamics are initial off-center and wedge difference. The wedge is realized using the expansion of deformation process. To test validation of a simulator, PID controller is tested.

Multicriteria Adaptive Observers for Singular Systems with Unknown Time-Varying Parameters

This paper proposes multicriteria adaptive observers for a class of singular systems with unknown time-varying parameters. Two criteria for the disturbance attenuation level and the upper bound of an ultimate invariant set are scalarized into a single cost function and then it is minimized by varying the weight parameter, which creates the optimal trade-off curve or Pareto optimal points. The proposed multicriteria adaptive observers are shown to be able to easily include integral action for better robust performance. It is demonstrated with numerical simulations that the proposed multicriteria adaptive observers provide the good estimation accuracy and allow effective and compromising design by considering two different cost functions simultaneously.

Deep learning based modeling for the lateral movement of a strip in hot finishing mill

In this paper, the problem of system identification for the lateral motion of a strip in hot finishing mill is investigated. The movement is affected by various asymmetric factors with respect to rolling force. Not only that, the tension between rolling mills determines the direction of strips moving. Consequently, the movement of a strip is complex dynamics with rolling condition, tension and other phenomena. To identify a neural network type system model in the existence of both uncertain parameters and nonlinear signals, deep learning based modelling is employed.

State dependent disturbance compensation method for motor control system with unknown input time delay

This paper proposes a periodic adaptive state dependent disturbance observer (PASDDOB) for motor control with the unknown input time delay, known output time delay and unknown phase delay from Q-filter to compensate the state dependent disturbance (SDD) that changes slowly by time. The PASDDOB has a structure that combines the state dependent disturbance observer (SDDOB) with the periodic adaptive learning compensation (PALC). The SDDOB compensates the known output delay and the unknown phase delay from Q-filter. The PALC compensates the unknown input time delay and the time-varying SDD. Therefore, the PASDDOB can compensate the SDD. The effectiveness of the proposed state dependent disturbance compensation method is demonstrated using MATLAB simulation results.

Decentralized H∞ control of large-scale descriptor systems using proportional-plus-derivative state feedback

This paper is concerned with the problem of decentralized H∞ proportional-plus-derivative(PD) state feed-back control of uncertain large-scale descriptor systems. The uncertainties are assumed to be polytopic type and appearing in derivative matrices as well as state and input matrices. Sufficient condition for stabilization of uncertain large-scale descriptor systems via H∞ PD state feedback is addressed in terms of Linear Matrix Inequalities(LMIs). A numerical example is given to prove the effectiveness of the proposed control method.

Decentralized guaranteed cost control for uncertain large-scale singular systems via proportional-plus-derivative state feedback

In this paper, decentralized guaranteed cost control for uncertain large-scale singular systems are studied. The parametric uncertainty which is assumed be norm-bounded exists not only in system matrices, but also in a derivative matrix. For the stabilization of the given system, guaranteed cost proportionalplus-derivative state feedback is suggested. The linear matrix inequality (LMI) condition which guarantees quadratic performance index is given. Numerical examples are shown to validate the proposed control.

Uniformly ultimately boundedness stability condition of systems with state delay and input backlash

In this paper, stability of linear systems with state delay and input backlash is investigated. The uniformly ultimately boundedness stability condition of the given system is constructed in terms of linear matrix inequalities (LMI) form which can be easily solved with off the shelf tool. Sufficient condition for the stability is provided. Numerical examples are stated in accordance with the results.