• Proceedings of the KSME Conference
• /
• 2003.11a
• /
• pp.1458-1463
• /
• 2003

This paper presents an improved identification algorithm of active magnetic bearing rotor systems considering sensor and actuator dynamics. An AMB rotor system has both real and complex poles so that it is very hard to identify them together. In previous research, a linear transformation through a fictitious proportional feedback was used in order to shift the real poles close to the imaginary axis. However, the identification result highly depends on the fictitious feedback gain, and it is not easy to identify the additional dynamics including sensor and actuators at the same time. First, this paper discusses the necessity and a selection criterion of the fictitious feedback gain. An appropriate feedback gain minimizes dominant SVD(Singular Value Decomposition) error through maximizing rank deficiency. Second, more improvement in the identification is achieved through separating the common additional dynamics in all elements of frequency response matrix. The feasibility of the proposed identification algorithm is proved with two theoretical AMB rotor models. Finally, the proposed scheme is compared with previous identification methods using experimental data, and a great improvement in model quality and large amount of time saving can be achieved with the proposed method.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.6
• /
• pp.782-787
• /
• 2006

The role of Unmanned Aircraft Vehicles(UAVs) has been increasing significantly in both military and civilian operations. Many complex systems, such as UAVs, are difficult to model accurately because they exhibit nonlinearity and show variations with time. Therefore, the control system must address the issues of uncertainty, nonlinearity, and complexity. Hence, identification of the mathematical model is an important process in controller design. In this paper, attitude dynamics identification of UAV is investigated. Using the flight data, nonlinear state space model for attitude dynamics of UAV is derived and verified. Real time simulation results show that the model dynamics match experimental data.

• Proceedings of the KIEE Conference
• /
• 1999.11c
• /
• pp.821-823
• /
• 1999

This paper describes a study on a person identification system which can improve currently available biometric systems. In the procedure of PIN(Personal Identification Number) input, holding time, interkey time between key presses are measured and normalized. Person identification is performed by matching using Euclidean distance of these punching dynamics. The experimental results show the possibility of improvement of the overall system performance when keypad dynamics feature is applied to the biometric systems which take PIN input using keypads.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2002.10a
• /
• pp.624-627
• /
• 2002

Experimental study showed that the existing mathematical model doesn't fully describe the lateral motion of a moving web fur different operating conditions. So, a physically interpretable model of lateral motion of a moving web in a typical web guidance system, operated at Konkuk Univ., was developed using the system identification technique. A well-known Least Square Method based on ARX model was used for the system identification. Lateral displacement of the web was measured at the exit of each span by infrared sensors. The model obtained from identifying a linear time-invariant system for a typical operating condition yields an improved prediction capability of the lateral dynamics of the moving web compared to other mathematical models proposed in literature.

• Proceedings of the KSME Conference
• /
• 2000.04a
• /
• pp.493-498
• /
• 2000

The magnetic bearing systems are intrinsically unstable, and need the feedback control of electromagnetic forces with measured displacements. So the controller design plays an important role in constructing high performance magnetic bearing system. In case of magnetic bearing systems, the order of identified model is high because of unknown dynamics included in closed loop systems - such as sensor dynamics, actuator dynamics-and non-linearity of magnetic bearings itself. "Identification for control" - joint optimization of system identification and controller design- is proposed to get the limited-order model which is suited for the design of high-performance controller. We applied the joint identification/controller design scheme to MIMO rigid rotor system supported by magnetic bearings. Firs, we designed controller of a nonlinear simulation model of MIMO magnetic bearing system with this scheme and proved its feasibility. Then, we performed experiments on MIMO rigid rotor system supported by magnetic bearings, and the performance of closed-loop system is improved gradually during the iteration.

• Journal of the Korean Society for Precision Engineering
• /
• v.31 no.12
• /
• pp.1147-1154
• /
• 2014

Generally, motor controller design is based on its motor dynamics. Therefore, it requires precise information of its motor dynamics. However, most of the low cost DC motors, which are widely used in industries and academia, are provided without such precise information. Even if it is given, the information is mostly imprecise. Following circumstances require one to calculate the motor dynamics information for oneself. This paper presents a simple method to readily apprehend the DC motor dynamics. First, how to establish the model of DC motor dynamics along with the model parameter identification is presented. Then, the parameter values are finetuned until the simulation response based on the dynamics model is close to the experimental response of the motor. Finally, the controller is designed with the established dynamics model. The validity of the designed controller is confirmed by the comparison of the experiment and simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.3-6
• /
• 2000

The magnetic bearing system are intrinsically unstable, and need the feedback control of electromagnetic forces with measured displacements. So the controller design plays an important role in constructing high performance magnetic bearing system. In case of magnetic bearing system, the order of identified model is high because of unknown dynamics included in closed loop systems - such as sensor dynamics, actuator dynamics - and non-linearity of magnetic bearings itself. In this paper the identification and robust control of flexible rotor supported by magnetic bearing are discussed. We measure and identify overall system that contains not only flexible rotor model but also magnetic bearing and time delay. The structured and unstructured uncertainties are modeled that cover variations of natural frequencies, uncertainties in sensor and actuator gains and unmodeled dynamics. And desired performances are specified with several weighting function. Using augmented system that includes identified model, uncertainties, and weighting functions, μ-synthesis is applied to flexible rotor supported with magnetic bearing. The flexible rotor was spin up over the first flexible critical speed.

• Journal of Power System Engineering
• /
• v.20 no.2
• /
• pp.58-65
• /
• 2016

Lately, tugboats are widely used to maneuver vessels by pushing or towing them where tugboats use rope. In order to correctly control the motion of tugboat and towed vessel, the dynamics of the towline would be well identified. In real application environment, the towing rope length changes and the towing load is not constant due to the various sizes of towed vessel. And there are many ropes made by many types of materials. It means that it is not easy to obtain rope dynamics, such that it is too difficult to satisfy the given control purpose by designing control system. Thus real time identification or adaptive control system design method may be a solution. However it is necessary to secure sufficient information about rope dynamics to obtain desirable control performance. In this paper, the authors try to have several rope dynamic models by changing the rope length to consider real application conditions. Among them, a representative model is selected and the others are considered as uncertain models which are considered in control system design. The authors design a robust control to cope with strong uncertain and nonlinear property included in the real plant. The designed control system based on robust control framework is evaluated by simulation.

• Journal of the Society of Naval Architects of Korea
• /
• v.48 no.1
• /
• pp.8-14
• /
• 2011

RIB(Rigid Inflatable Boat) is widely used for coastal transportation in the commercial use and for ISR(Intelligence, Surveillance, Reconnaissance) in the military use. Since RIB is around 10 meters in length and over 30 knots in speed, its motion characteristics in waves is quite different from a large scale ship. When it turns, large roll occurs and heeling direction is opposite to the large ship's case. Currently, many countries are developing USV(Unmanned Surface Vehicle) of which type is RIB. In order to develop high performance autopilot and way point controller, it is very important to identify RIB's motion characteristics. In this paper, sea trial test results of a 7-meter RIB such as speed, turning, zig-zag, and way point control tests were represented and its resistance and propulsion model was identified by using sea trial data and Savitsky's formula. In addition, the state space model which will be used in the identification of the four-degree-of-freedom dynamics in the next step was formulated and the identification procedure was proposed.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.299-303
• /
• 1995

This paper charcterizes dynamics of cold tandem minns, and constructs it state-space model of which are linear time invariant, using subspace method. Step responses particularly show the influence on mass transfer delay. Input-output data set are obtained form nonlinear differential equations including mass transfer delay and nonlinearity. It is shown that the identified state-apace model well approximates the original systems dynamics.