• Industrial Engineering and Management Systems
• /
• v.15 no.1
• /
• pp.63-76
• /
• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.119-122
• /
• 1996

The recently proposed control method using a Lyapunov-like function can give global asymptotic stability to a system with mismatched uncertainties if the uncertainties are bounded by a known function and the uncontrolled system is locally and asymptotically stable. In this paper, we modify the method so that it can be applied to a system not satisfying the latter condition without deteriorating qualitative performance. The assured stability in this case is uniform ultimate boundedness which is as useful as global asymptotic stability in the sense that it is global and the bound can be taken arbitrarily small. By the proposed control law we can deal with both matched and mismatched uncertain systems. The above facts conclude that Lyapunov-like control method is superior to any other Lyapunov direct methods in its applicability to uncertain systems.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.4
• /
• pp.413-419
• /
• 2009

A decentralized adaptive control method is proposed for large-scale systems with unknown time-delayed nonlinear interconnections unmatched in control inputs. It is assumed that the time-delayed interaction terms are bounded by unknown nonlinear bounding functions. The nonlinear bounding functions and uncertain nonlinear functions of large-scale systems are compensated by the function approximation technique using neural networks. The dynamic surface control method is extended to design the proposed memoryless local controller for each subsystem of uncertain nonlinear large-scale time delay systems. Therefore, although the interconnected systems consist of a large number of subsystems, the proposed controller can be designed simply. We prove that all the signals in the total closed-loop system are semiglobally uniformly bounded and the control errors converge to an adjustable neighborhood of the origin. Finally, an example is given to demonstrate the effectiveness and applicability of the proposed scheme.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.401-404
• /
• 1998

In this paper, we present robust reliable $H\infty$ controller design methods of continuous and discrete uncertain time delay systems through LMI(linear matrix inequality) approach, respectively. Also the existence conditions of state feedback control are proposed. Using some changes of varables and Schur complements, the obtained sufficient conditions are transformed into LMI form. We show the validity of the proposed method through numerical examples.

• Proceedings of the KIEE Conference
• /
• 2003.11b
• /
• pp.131-134
• /
• 2003

In this paper, we consider the problem of finding the stability region in state space for uncertain linear systems with input saturation. For stability analysis, two Lyapunov functions are chosen. One is for the lineal region and the other is for the saturated legion. Piecewise Lyapunov functions are obtained by solving successive linear matrix inequalites(LMIs) relaxations. A sufficient condition for robust stability is derived in the form of stability region of initial conditions. A numerical example shows the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
• /
• 1999.11c
• /
• pp.469-471
• /
• 1999

In this paper, a dynamic output feedback controller design technique for robust decentralized stabilization of uncertain large-scale systems is presented. Based on the Lyapunov method, a sufficient condition for robust stability, is derived in terms of three linear matrix inequalities(LMIs). The solutions of the LMIs can be easily obtained using efficient convex optimization techniques.

• Proceedings of the KIEE Conference
• /
• 1989.07a
• /
• pp.57-61
• /
• 1989

An adaptive control scheme is presented for uncertain systems whose uncertaintiy bounds are expressed as a linear combination of unknown functions of special form. Both the states and the parameter estimate errors of the closed-loop system are proven to be bounded. The regulation errors can be made sufficiently small by adjusting the design parameters. An application of the proposed method to the position control of a simple pendulum is given.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.589-591
• /
• 1999

In this paper, we consider the robust pole assignment for linear system with time-varying uncertainty. The considered uncertainty is an unstructured uncertainty. Based on Lyapunov stability and linear matrix inequality technique, we present a condition that guarantees the robust pole assignment inside a circular disk and the robust stability of uncertain linear systems. Finally, we show the usefulness of our results by an example.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.52-54
• /
• 1991

In this paper, the robust stability, and the quadratic performance of linear uncertain systems are studied. A quadratic Lyapunov function candidate with time-varying matrix is derived to provide robust stability bounds. Also upper bounds of a quadratic performance is given under the assumption that the uncertain system is stable. Both the robust stability bounds and the upper bounds of a quadratic performance are obtained as solutions of a class of modified Lyapunov equations.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.687-693
• /
• 1989

A robust deterministic control for a class of singularly perturbed uncertain systems, where uncertainties are characterized deterministically rather than stochastically, is developed based mainly on information available on an uncertain reduced-order system. The deterministic control scheme is applied to the motion control of a n degree of freedom robotic manipulator. The parasitic actuator and sensor dynamics of the manipulator are explicitly considered in the stability analysis of the deterministic controller using a singular perturbation model. Simulation and experimental studies for a two degree of freedom, direct drive SCARA manipulator are conducted to evaluate the effectiveness of the derived control scheme.