• Proceedings of the KIEE Conference
• /
• 1992.07a
• /
• pp.305-307
• /
• 1992

This paper presents a technique, which identifies both process noise covariance and sensor noise covariance by using innovation correlation test. A correlation test, which checks whether the square root Kalman filter is workingly optimal or not, is given. The system is stochastic autoregressive moving-average model with auxiliary white noise Input. The linear quadratic Gaussian control is used for minimizing stochastic cost function. This paper indentifies Q, R, and estimates parametric matrics $A(q^{-1}),B(q^{-1}),C(q^{-1})$ by means of extended recursive least squares and model reference control. And The proposed technique has been validated in simulation results on the fourth order system.

• International Journal of Precision Engineering and Manufacturing
• /
• v.5 no.3
• /
• pp.77-84
• /
• 2004

A robust optimal control design is proposed in this study for rigid robotic systems under the unknown loads and the other uncertainties. The uncertainties are reflected in the performance index, where the uncertainties are bounded for the quadratic square of the states with a positive definite weighting matrix. An iterative algorithm is presented for the determination of the weighting matrix required for necessary robustness. Computer simulations have been done for a weight-lifting operation of a two-link manipulator and the simulation results shows that the proposed algorithm is very effective for a robust control of robotic systems.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.3
• /
• pp.451-458
• /
• 2012

This paper addresses the problem that policy iteration (PI) for continuous-time (CT) systems requires explorations of the state space which is known as persistency of excitation in adaptive control community, and as a result, proposes a PI scheme explorized by an additional probing signal to solve the addressed problem. The proposed PI method efficiently finds in online fashion the related CT linear quadratic (LQ) optimal control without knowing the system matrix A, and guarantees the stability and convergence to the LQ optimal control, which is proven in this paper in the presence of the probing signal. A design method for the probing signal is also presented to balance the exploration of the state space and the control performance. Finally, several simulation results are provided to verify the effectiveness of the proposed explorized PI method.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.3
• /
• pp.281-292
• /
• 2006

The design and implementation of Generalized Minimum Variance control laws for nonlinear multivariable systems that can include severe nonlinearities is considered. The quadratic cost index minimised involves dynamically weighted error and nonlinear control signal costing terms. The aim here is to show the controller obtained is simple to design and implement. The features of the control law are explored. The controller obtained includes an internal model of the process and in one form is a nonlinear version of the Smith Predictor.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.11 no.4
• /
• pp.91-102
• /
• 1991

Traditionally, a dynamic programming(DP) technique has been used to the multireservoir control system. The algorithm has inherent problem to increase computational requirements exponentially due to discretization of variables and expanding the dimension of the system. To solve this problem, this paper describes transforming the optimal control system into a quadratic programming(QP), using Laguerre polynomials(LP) and its properties. The objective function of the proposed QP is independent of time variable. The solution of the QP is obtained by nonlinear programming(NLP) using augmented Lagrangian multiplier method. The numerical experiment shows that the water level of reservoirs is higher than Lee's and the evaluated benefit value is about the same as other researcher's.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.24 no.2
• /
• pp.52-60
• /
• 2020

This paper deals with an optimal output tracking control for open-cycle liquid propellant rocket engine. For this purpose, we modeled simplified mathematical model of open-cycle liquid propellant rocket engine and designed optimal output feedback control system using combustion chamber pressure. For design the closed-loop system of open-cycle liquid propellant rocket engine, we designed optimal output feedback linear quadratic tracking control system using the linearized model and demonstrated the performance of the controller through numerical simulation.

• Journal of Mechanical Science and Technology
• /
• v.16 no.9
• /
• pp.1166-1174
• /
• 2002

This paper presents the implementation and vehicle tests of a vehicle longitudinal control scheme for Stop and Go cruise control. The control scheme consists of a vehicle-to-vehicle distance control algorithm and throttle/brake control algorithm for acceleration tracking. The desired acceleration of a vehicle for vehicle-to-vehicle distance control has been designed using Linear Quadratic optimal control theory. Performance of the control algorithm has been investigated via vehicle tests. A millimeter wave radar sensor has been used for distance measurement. A stepper motor and an electronic vacuum booster have been used for throttle/brake actuators, respectively. It has been shown that the proposed control algorithm can provide satisfactory performance.

• Nuclear Engineering and Technology
• /
• v.21 no.2
• /
• pp.99-110
• /
• 1989

The optimal control of xenon concentration in a nuclear reactor is posed as a linear quadratic regulator problem with state feedback control. Since it is not possible to measure the state variables such as xenon and iodine concentrations directly, implementation of the optimal state feedback control law requires estimation of the unmeasurable state variables. The estimation method used is based on the Luenberger observer. The set of the reactor kinetics equations is a stiff system. This singularly perturbed system arises from the interaction of slow dynamic modes (iodine and xenon concentrations) and fast dynamic modes (neutron flux, fuel and coolant temperatures). The singular perturbation technique is used to overcome this stiffness problem. The observer-based controller of the original system is effected by separate design of the observer and controller of the reduced subsystem and the fast subsystem. In particular, since in the reactor kinetics control problem analyzed in the study the fast mode dies out quickly, we need only design the observer for the reduced slow subsystem. The results of the test problems demonstrated that the state feedback control of the xenon oscillation can be accomplished efficiently and without sacrificing accuracy by using the observer combined with the singular perturbation method.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.34 no.5
• /
• pp.173-178
• /
• 1985

The control of a linear system with random coefficients is discussed here. The cost function is of a quadratic form and the random coefficients are assumed to be completely observable by the controller. Stochastic Process involved in the problem by the controller. Stochastic Process involved in the problem formulation is presented to be the unique strong solution to the corresponding stochastic differential equations. Condition for the optimal control is represented through the existence of solution to a Cauchy problem for the given nonlinear partial differential equation. The optimal control is shown to be a linear function of the states and a nonlinear function of random parameters.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2008.11a
• /
• pp.736-742
• /
• 2008

This paper proposes new searching algorithm for the optimal PD gains of flexible rotor supported by active magnetic bearings. Under the assumption of linearized bearing parameters with respect to PD gains, the performance index in quadratic form is defined and steepest descent method is adopted for determining local minimum. Moreover, the eigenpair sensitivity concept is utilized to evaluate the sensitivity of performance index. To evaluate the effectiveness of suggested algorithm, the finite element model is constructed and its reduced model is retained in modal domain. Given starting gains, the optimal gains are successfully found and the control performance is demonstrated by simulation to show the efficiency of the proposed method.