• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.3
• /
• pp.300-304
• /
• 2012

This paper presents a nonlinear observer design method for SOC(state-of-charge) estimation of Lithium polymer battery cell. The dynamic equation of the battery cell is modeled as a simple RC electrical circuit with a nonlinear voltage source and the parameters are obtained via nonlinear optimization. Using the sum of squares decomposition, the observer gain is designed such that the error dynamics is asymptotically stable and the decay rate is below the prescribed value. In order to illustrate the performance of the observer, a computer simulation is performed using the experimental data with the UDDS(urban dynamometer driving schedule) current profile.

• Proceedings of the KAIS Fall Conference
• /
• 2006.05a
• /
• pp.307-310
• /
• 2006

We consider the problem of constructing observers for nonlinear systems with unknown inputs. It is shown that under some conditions, there exists an observer estimating the states of nonlinear systems with unknown inputs. Nonlinear observer design method using observer error linearization and the design technique of unknown input observer(UIO) for linear systems are used to derive conditions. Some illustrative examples are included. In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller.The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.12
• /
• pp.2292-2297
• /
• 2010

To improve the performances of Sawyer motors and to regulate yaw rotation, various feedback control methods have been developed. Almost all of these methods require information on the position, velocity or full state of the motor. Therefore, in this paper, a nonlinear observer is designed to estimate the full state of the four forcers in a Sawyer motor. The proposed method estimates the full state using only positional feedback. Generally, Sawyer motors are operated within a yaw magnitude of several degrees; outside of this range, Sawyer motors step out. Therefore, this observer design assumes that the yaw is within ${\pm}90^\b{o}$. The convergence of the estimation error is proven using the Lyapunov method. The proposed observer guarantees that the estimation error globally exponentially converges to zero for all arbitrary initial conditions. Furthermore, since the proposed observer does not require any transformation, it may result in a reduction in the commutation delay. The simulation results show the performance of the proposed observer.

• Journal of IKEEE
• /
• v.11 no.4
• /
• pp.213-218
• /
• 2007

We consider a web transport system. The objective of this paper is to design the output feedback controller such that the controller can track a desired tension and processing speed on web transport system. We propose the new design method using observer and feedback linearization technique. The proposed method use a nonlinear feedback to transform to linear system and high gain observer to estimate the state value. We show that the proposed controller can achieve the control object using only output. We show a performance of controller via the simulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.27-27
• /
• 2000

The nonlinear observers are proposed for a nonlinear system. To improve the characteristics such as a stability, a convergence, and an H$\sub$$\infty$/ filter performance criterion, we utilize and H$\sub$$\infty$/ filter Riccati equation or a modified H$\sub$$\infty$/ filter Riccati equation with a freedom parameter. Using the Lyapunov, the characteristics of the observer are analyzed. Then the in-flight alignment for a strapdown inertial navigation system(SDINS) is designed using the observer proposed. Simulation results show that the observer with the modified H$\sub$$\infty$/ fitter Riccati equation effectively improve the performance of the in-flight alignment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.6
• /
• pp.411-416
• /
• 2016

This paper presents the design methodology of an unknown input observer for Lipschitz nonlinear systems with unknown inputs in the framework of convex optimization. We use an unknown input observer (UIO) to consider both nonlinearity and disturbance. By deriving a sufficient condition for exponential stability in the linear matrix inequality (LMI) form, existence of a stabilizing observer gain matrix of UIO will be assured by checking whether the quadratic stability margin of the error dynamics is greater than the Lipschitz constant or not. If quadratic stability margin is less than a Lipschitz constant, the coordinate transformation may be used to reduce the Lipschitz constant in the new coordinates. Furthermore, to reduce the maximum singular value of the observer gain matrix elements, an object function to minimize it will be optimally designed by modifying its magnitude so that amplification of sensor measurement noise is minimized via multi-objective optimization algorithm. The performance of UIO is compared to a nonlinear observer (Luenberger-like) with an application to a flexible joint robot system considering a change of load and disturbance. Finally, it is validated via simulations that the estimated angular position and velocity provide true values even in the presence of unknown inputs.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• 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.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.39.2-39
• /
• 2001

This paper describes the design of an output-feedback controller based on an adaptive fuzzy observer for uncertain single-input single-output nonlinear dynamical systems. Especially, we have focused on the realization of minimal dynamic order of the adaptive fuzzy observer. For the purpose, we propose a new method in which no strictly positive real(SPR) condition is needed and combine dynamic rule activation scheme with on-line estimation of fuzzy parameters. By using proposed scheme, we can reduce computation time, storage space, and dynamic order of the adaptive fuzzy observer ...

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.41 no.4
• /
• pp.284-290
• /
• 2013

The authors propose a nonlinear unknown input observer to estimate the angular speed of a satellite and to detect faults of reaction wheels. Input values are necessary to estimate the angular speed. Therefore, estimation errors are inevitable if faults occur in actuators or reaction wheels. Unknown input observers are useful to estimate the states of a system without being affected by unknown faults. The authors have designed a nonlinear unknown input observer by using the SDRE method and verified the proposed observer via numerical simulations. In spite of various and simultaneous faults, we have estimated the states and detected faults exactly by the proposed nonlinear unknown input observer.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.15 no.4
• /
• pp.282-287
• /
• 2010

This paper proposes a new nonlinear speed controller with a fuzzy load torque observer based on the Takagi-Sugeno fuzzy method for a permanent magnet synchronous motor(PMSM). The LMI conditions are derived for the existence of the proposed nonlinear speed controller and fuzzy load torque observer, and the LMI parameterization to obtain the gain matrices of the controller and observer is given. In this paper, to verify the performance of the proposed nonlinear speed controller and fuzzy load torque observer, and the simulation and experimental results are demonstrated under motor parameter and load torque variations.