• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.995-1000
• /
• 2004

A digital adaptive flight control system is presented for a Japanese automatic landing flight experiment vehicle (ALFLEX). In previous adaptive control systems based on a linear-parameter-varying (LPV) form, the output behavior was excellent, while the behavior of the adjusted parameters was unsatisfactory. In the present study, to obtain a more appropriate parameter adjustment law, the relationship between the coefficient matrices in a continuous-time state equation and the coefficients of a pulse transfer function in a discrete system for conventional aircraft is investigated. As a result, it is revealed that the coefficients of the numerator can be treated as a linear function of dynamic pressure (linear-parameter-varying: LPV), while the coefficients of the denominator can be treated as constant (linear-time-invariant: LTI). From the above analysis, an improved parameter adjustment law is derived by reducing the number of the adjustment parameters. Simulation results also revealed both good output tracking and good parameter adjustment compared with the previous results.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.535-535
• /
• 2000

This paper presents an adaptive receding horizon H$_{\infty}$ controller for the linear parameter varying systems in the deterministic environment, which combines a parameter range estimator and a robust receding horizon H$_{\infty}$ controller using the parameter bounds. Using parameter set inclusion and terminal inequality condition, the closed-loop system stability is guaranteed. It is shown that the stabilizing adaptive receding horizon H$_{\infty}$ controller guarantees the H$_{\infty}$ norm bound.

• 전기학회논문지
• /
• 제67권2호
• /
• pp.308-313
• /
• 2018

In this paper, we propose a sampled-data model predictive tracking control deign for leader-following control of multi-mobile robot system. The error dynamics of leader-following robots is modeled as a Linear Parameter Varying (LPV) model. Also, the Lyapunov function is presented to guarantee stability of the networked control system. Based on the stabilization condition using a quadratic Lyapunov function approach, model predictive sampled-data controller is designed. Finally, the leader-following control of multi mobile robots is simulated to show effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.148.5-148
• /
• 2001

In this report, an adaptive flight control law based on a linear-parameter-varying (LPV) model is presented for a flight control system. The control system is designed to track an output of a vehicle to a reference signal from the guidance system, which generates a reference flight path. The proposed adaptive control law adjusts the controller gains continuously on line as flight conditions change. The obtained adaptive controller guarantees global stability over a wide flight envelope. Computer simulation involving six-degree-of-freedom nonlinear flight dynamics is applied to Japan´s automatic landing flight experimental vehicle (ALFLEX) to examine the effectiveness of the proposed adaptive flight control law.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1871-1876
• /
• 2005

In this paper, We present a new nonlinear adaptive control law using a disturbance accommodating control (DAC) observer for a Japanese automatic landing flight experiment vehicle called ALFLEX. A future spaceplane must have ability to deal with greater fluctuations in the stability and control derivatives of flight dynamics, because its flight region is much wider than that of conventional aircraft. In our previous studies, digital adaptive flight control systems have been developed based on a linear-parameter-varying (LPV) model depending on dynamic pressure, and obtained good simulation results. However, under previous control laws, it is difficult to accommodate uncertainties represented by disturbance and nonlinearity, and to design a stable flight control system. Therefore, in this study, we attempted to design a nonlinear adaptive control law using the DAC Observer and inverse dynamic methods. A good tracking property of the obtained system was confirmed in numerical simulation.

• International Journal of Automotive Technology
• /
• 제8권4호
• /
• pp.445-453
• /
• 2007

This paper presents a robust controller design approach for improving vehicle dynamic roll motion performance and guaranteeing the closed-loop system stability in spite of vehicle parameter variations resulting from aging elements, loading patterns, and driving conditions, etc. The designed controller is linear parameter-varying (LPV) in terms of the time-varying parameters; its control objective is to minimise the $H_{\infty}$ performance from the steering input to the roll angle while satisfying the closed-loop pole placement constraint such that the optimal dynamic roll motion performance is achieved and robust stability is guaranteed. The sufficient conditions for designing such a controller are given as a finite number of linear matrix inequalities (LMIs). Numerical simulation using the three-degree-of-freedom (3-DOF) yaw-roll vehicle model is presented. It shows that the designed controller can effectively improve the vehicle dynamic roll angle response during J-turn or fishhook maneuver when the vehicle's forward velocity and the roll stiffness are varied significantly.

• 전자공학회논문지S
• /
• 제34S권11호
• /
• pp.73-79
• /
• 1997

This paepr is concerned with the design of linear parameter varying filter that ensures H$^{2}$/$H^{\infty}$ performance for a class of linear parameter varying(LPV) plants. The state space matrices of plant are assumed to be dependent affinely on a vector of time varying parameter, and each parameter is assumed to be measured in real time. Using the linear matrix inequalities(LMIs), we can solve the synthesis problem and the solution of LMIs is carried out off-line. The designed filter is parameter varying and automatically scheduled along parameter trajectories. Because the solution of LMIs is carried out off-line, computation time of filter gain is reduced. The validity of the proposed algorithm is verifed through computer simulation..

• 전기학회논문지
• /
• 제66권2호
• /
• pp.387-393
• /
• 2017

This paper focuses on a horizontal waypoint tracking and a speed control of large diameter unmanned underwater vehicles (LDUUVs) with X-stern configuration plane. The concerned design problem is converted into an asymptotic stabilization of the error dynamics with respect to the desired yaw angle and surge speed. It is proved that the error dynamics under the proposed control scheme based on the linear control and the feedback linearization can be considered as a cascade system; the cascade system is asymptotically stable if its nominal systems are so. This stability connection enables to separately deal with the waypoint tracking problem and the speed control one. By using the sector nonlinearity, the nominal system with nonlinearities is modeled as a polytopic linear parameter varying (LPV) system with parametric uncertainties. Then, sufficient linear matrix inequality (LMI) conditions for its asymptotic stabilizability are derived in the sense of Lyapunov stability criterion. An example is given to show the validity of the proposed methodology.

• 제어로봇시스템학회논문지
• /
• 제7권1호
• /
• pp.1162-1170
• /
• 2001

This paper proposes a practical gain-scheduling control law considering robust stability and performance of Linear Parameter Varying(LPV) systems in the presence of nonlinearities and uncertainties. The proposed method introduces LMI-based pole placement synthesis and also associates with a recently developed fuzzy control system based on Takagei-Sugenos fuzzy model. The sufficient conditions for robust controller design of linearized local dynamics and robust stabilization of fuzzy control systems are reduced to a finite set of Linear Matrix inequalities(LMIs) and solved by using co-evolutionary algorithms. The proposed method is applied to the longitudinal acceleration control of high performance aircraft with linear and nonlinear simulations.