• Journal of applied mathematics & informatics
• /
• v.30 no.5_6
• /
• pp.699-717
• /
• 2012

In this paper, we deal with the robust mixed $H_2/H_{\infty}$ guaranteed-cost control problem involving uncertain neutral stochastic distributed delay systems. More precisely, the aim of this problem is to design a robust mixed $H_2/H_{\infty}$ guaranteed-cost controller such that the close-loop system is stochastic mean-square exponentially stable, and an $H_2$ performance measure upper bound is guaranteed, for a prescribed $H_{\infty}$ attenuation level ${\gamma}$. Therefore, the fast convergence can be fulfilled and the proposed controller is more appealing in engineering practice. Based on the Lyapunov-Krasovskii functional theory, new delay-dependent sufficient criteria are proposed to guarantee the existence of a desired robust mixed $H_2/H_{\infty}$ guaranteed cost controller, which are derived in terms of linear matrix inequalities(LMIs). Furthermore, the design problem of the optimal robust mixed $H_2/H_{\infty}$ guaranteed cost controller, which minimized an $H_2$ performance measure upper bound, is transformed into a convex optimization problem with LMIs constraints. Finally, two simulation examples illustrate the design procedure and verify the expected control performance.

• Nuclear Engineering and Technology
• /
• v.35 no.5
• /
• pp.399-411
• /
• 2003

A model predictive control method is applied to design an automatic controller for thermal power control in a reactor core. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the second optimal control input is not implemented and the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize the difference between the output and the desired output and the variation of the control rod position. The nonlinear PWR plant model (a nonlinear point kinetics equation with six delayed neutron groups and the lumped thermal-hydraulic balance equations) is used to verify the proposed controller of reactor power. And a controller design model used for designing the model predictive controller is obtained by applying a parameter estimation algorithm at an initial stage. From results of numerical simulation to check the controllability of the proposed controller at the $5\%/min$ ramp increase or decrease of a desired load and its $10\%$ step increase or decrease which are design requirements, the performances of this controller are proved to be excellent.

• Journal of Electrical Engineering and information Science
• /
• v.3 no.3
• /
• pp.306-315
• /
• 1998

In this paper, a unified approach to the H\ulcorner controller design is proposed under the $\delta$-form for both continuous and discrete systems. Most of important basic concepts of H\ulcorner control, such as inner, co-inner, GCARE and GFARE, are reformulated by the unified form. The NLCF(Normalized left Comprime Factor) plant description has been reviewed in the $\delta$-form, and some corresponding results are proposed. And the unified H\ulcorner controller is designed which is based on the McFarlane and Glover{1]. The state-space parameterization for all suboptimal controllers is given under the NLCF model which may not be strictly proper, and the central controller is derived by using the solution to Hankel norm approximation problem[2]. The unified controller is applied to the industrial boiler control problem to exemplify the performance of the controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.898-902
• /
• 2003

For linear descriptor systems, we consider the $H_{INFTY}$ controller design problem via output feedback. Both static output feedback and dynamic one are discussed. First, in the case of static output feedback, we reduce our control problem to solving a bilinear matrix inequality (BMI) with respect to the controller coefficient matrix, a Lyapunov matrix and a matrix related to the descriptor matrix. Under a matching condition between the descriptor matrix and the measured output matrix (or the control input matrix), we propose setting the Lyapunov matrix in the BMI as being block diagonal appropriately so that the BMI is reduced to LMIs. For fixed-order dynamic $H_{INFTY}$ output feedback, we formulate the control problem equivalently as the one of static output feedback design, and thus the same approach can be applied.

• Proceedings of the KIEE Conference
• /
• 2008.10b
• /
• pp.462-463
• /
• 2008

This paper proposes a method for dynamic output-feedback controller design for stochastic time-delay systems. Based on recent results on time-delay systems control, a tractable and delay-dependent design condition is proposed, which provides a dynamic output-feedback controller to render the closed-loop stochastic time-delay systems to be asymptotically stable in the mean-square sense. The feasibility problem of the proposed condition is recast into a cone complementarity problem. An algorithm adopting cone complementarity linearization is presented to solve the resulting problem.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.729-731
• /
• 2004

This paper deals with the design of a low order $H_{\infty}$ controller by using an iterative linear matrix inequality (LMI) method. The low order $H_{\infty}$ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, a linear penalty function is incorporated into the objective function so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Numerical experiments show the effectiveness of the proposed algorithm.

• Journal of IKEEE
• /
• v.19 no.4
• /
• pp.520-525
• /
• 2015

This paper investigates the consensus problem for high-order integrators with an arbitrary large communication delay. In order to solve this problem, new consensus controller with an additional design parameter that can eliminate the effect of a communication delay on the consensus problem is proposed. Also, it is proved that the proposed consensus controller can always solve the consensus problem of high-order integrators even in the presence of an arbitrarily large communication delay. Finally, an illustrative example is given in order to show the effectiveness of our design method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.7
• /
• pp.1298-1301
• /
• 2007

The problem of designing dynamic output feedback sliding mode controllers for uncertain multivariable linear systems is considered. Using linear matrix inequalities(LMIs), a feasibility condition for the design problem is derived. Explicit fomulas of the gain matrices of a full order output feedback sliding mode controller in terms of the solution matrices of the LMI condition is given. A simple LMI-based algorithm for designing output feedback sliding mode controllers is also given. Finally, numerical design examples are given to show the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.44.1-44
• /
• 2002

This paper is concerned with the problem of designing a guaranteed cost state feedback controller for singular systems with time-varying delays. The sufficient condition for the existence of a guaranteed cost controller, the controller design method, and the optimization problem to get the upper bound of guaranteed cost function are proposed by LMI(linear matrix inequality), singular value decomposition, Schur complements, and change of variables. Since the obtained sufficient conditions can be changed to LMI form, all solutions including controller gain and upper bound of guaranteed cost function can be obtained simultaneously.

• Journal of Electrical Engineering and Technology
• /
• v.6 no.2
• /
• pp.182-191
• /
• 2011

Genetic algorithms (GA) and particle swarm optimization (PSO) are the most famous optimization techniques among various modern heuristic optimization techniques. These two approaches identify the solution to a given objective function, but they employ different strategies and computational effort; therefore, a comparison of their performance is needed. This paper presents the application and performance comparison of the PSO and GA optimization techniques for a static synchronous series compensator-based controller design. The design objective is to enhance power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem, and both PSO and GA optimization techniques are employed to search for the optimal controller parameters.