• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.19-24
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• 2003

A new method for designing critical control systems is proposed in this paper. The controller structure is chosen as a Davison type integral controller with an observer. The proposed method consists of two steps. First, the state feedback critical control system is designed using a quadratic performance index with tunable parameters. Second, the observer gain matrix is determined by the formal LTR procedure using a Riccati equation. Consequently, the search space can be reduced considerably compared with the conventional approach. Although the proposed method sacrifices a large freedom for the choice of controller structure provided by the principle of matching, the controller structure used in this paper is not excessively complex and can be used for most applications. An illustrative design example is presented.

• Smart Structures and Systems
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• v.20 no.1
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• pp.1-10
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• 2017

Ionic Polymer Metal Composite (IPMC) is an electroactive polymer (EAP) and a promising candidate actuator for various potential applications mainly due to its flexible, low voltage/power requirements, small and compact design, and lack of moving parts. Although widely used in industry, this material requires accurate numerical models and knowledge of optimal control methods. This paper presents State-Dependent Riccati Equation (SDRE) approach as one of rapidly emerging methodologies for designing nonlinear controllers. Additionally, the present paper describes a novel method of Multi HGO Observer design. In the proposed design, the calculated position of the IPMC strip accurately tracks the target position, which is illustrated by the experiments. Numerical results and comparison with experimental data are presented and the effectiveness of the proposed control strategy is verified in experiments.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.382-385
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• 1991

In order to stabilize linear time-invariant systems with the unknown system matrix, a piecewise constant linear state feedback control law including switching logic is developed. A number of feedback gain matrices are first precomputed by solving the Algebraic Riccati Equation with prescribed degree of stability, and then are switched over in a direction to increase degree of stability. Switching stops when a Lyapunov function shows the decreasing property, and hence switching times are finite.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.355-359
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• 1993

This paper deals with the problem of robust TDF(Two Degree of Freedom) H$_{\infty}$ control design for a linear system with parameter uncertainty in the state space model. The uncertain system considered here is with the time-invariant norm-bounded parameter uncertainty in the state matrix. A TDF H$_{\infty}$ control design is presented which robustly stabilizes the plant, guarantees the robust H$_{\infty}$ performance and improves the tracking performance for the closed-loop system in the face of parameter uncertainty. It is shwon that a suitable stabilizing control law can be constructed in terms of a positive definite solution to a certain parameter-dependent algebraic Riccati equation and a good tracking performance can be constructed in terms of suitable feedforward control law.aw.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1557-1569
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• 2011

In this paper, we consider the oscillation of the following certain second order nonlinear differential equations $(r(t)(x^{\prime}(t))^{\alpha})^{\prime}+q(t)x^{\beta}(t)=0$>, where ${\alpha}$ and ${\beta}$ are ratios of positive odd integers. New oscillation theorems are established, which are based on a class of new functions ${\Phi}={\Phi}(t,s,l)$ defined in the sequel. Also, we establish some interval oscillation criteria for this equation.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.67-74
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• 2015

Two-wheeled driying mobild robots are precise controlled in terms of linear contol methods without considering the nonlinear dynamical characteristics. However, in the high maneuvering situations such as fast turn and abrupt start and stop, such neglected terms become dominant and heavy influence the overall driving performance. This study describes the nonlinear optimal control method to take advantage of the exact nonlinear dynamics of the balancing robot. Simulation results indicate that the optimal control outperforms in the respect of transient performance and required wheel torques. A design example is suggested for the state matrix that provides design flexibility in the control. It is shown that a well-planned state matrix by reflecting the physics of a balancing robot greatly conrtibutes to the driving performance and stability.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.32.2-32.2
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• 2011

State dependent Riccati equation (SDRE) control technique has been widely used in the control society. Although it solves nonlinear optimal control problems, which minimizes state error and control efforts simultaneously, it has drawbacks when it is to be applied to the real time systems in that it requires much computational efforts. So the real time system whose computational ability is limited (for example, satellites) cannot afford to use SDRE controller. To solve this problem, a hybrid controller which is based on MSDRE (Modified SDRE) and ANFIS (Adaptive Neuro-Fuzzy Inference System) has been proposed by Abdelrahman et al. (2010). We propose a hybrid controller based on SDRE and ANFIS, and apply the hybrid controller to the hardware attitude simulator to perform a HIL (Hardware-In-the-Loop) simulation. Through HIL simulation, it is demonstrated that the hybrid controller satisfies the control requirement and the computation load is reduced significantly. In addition, the effects of statistical properties of the ANFIS training data to the performance of the ANFIS controller have been analyzed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.9
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• pp.922-929
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• 2009

This paper deals with the State-Dependent Riccati Equation (SDRE) Technique for the design of helicopter nonlinear waypoint guidance controller. To generate the flight guidance through multiple waypoints, we use the trigonometric spline. The controller design and its validation is based upon a level 2 simulation helicopter model and the designed SDRE controller is applied to the trajectory tracking problems. To validate the designed SDRE controller, the simulation environment of high fidelity helicopter model is developed using three independent computers. This paper focuses on the validation the present SDRE controller through the helicopter waypoint guidance simulation.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.12-22
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• 2009

This paper deals with the State-Dependent Riccati Equation (SDRE) Technique for the design of rotorcraft waypoint guidance. To generate the flight trajectory through multiple waypoints, we use the trigonometric spline. The controller design and its validation is based upon a level 2 simulation rotorcraft model and the designed SDRE controller is applied to the trajectory tracking problems. To verify the designed guidance law, the simulation environment of high fidelity rotorcraft model is developed using three independent PCs. This paper focuses on the validation of rotorcraft waypoint guidance law which is designed by using SDRE Controller.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.295-298
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• 1996

In this paper, a self-tuning optimal control algorithm is proposed to retain the optimal performance of an active suspension system, when the vehicle has some time varying parameters and parameter uncertainties. We consider a 2 DOF time-varying quarter car model which has the parameter variation of sprung mass, suspension spring constant and suspension damping constant. Instead of solving algebraic riccati equation on line, we propose a neural network approach as an alternative. The optimal feedback gains obtained from the off line computation, according to parameter variations, are used as the neural network training data. When the active suspension system is on, the parameters are identified by the recursive least square method and the trained neural network controller designer finds the proper optimal feedback gains. The simulation results are represented and discussed.