• Structural Engineering and Mechanics
• /
• 제20권5호
• /
• pp.543-558
• /
• 2005

The natural frequencies of a long span bridge vary during its construction and it is thus difficult to apply traditional tuned liquid column dampers (TLCD) with a fixed configuration to reduce bridge vibration. The restriction of TLCD imposed by frequency tuning requirement also make it difficult to be applied to structure with either very low or high natural frequency. A semi-active tuned liquid column damper (SATLCD), whose natural frequency can be altered by active control of liquid column pressure, is studied in this paper. The principle of SATLCD with adaptive tuning capacity is first introduced. The analytical models are then developed for lateral vibration of a structure with SATLCD and torsional vibration of a structure with SATLCD, respectively, under either harmonic or white noise excitation. The non-linear damping property of SATLCD is linearized by an equivalent linearization technique. Extensive parametric studies are finally carried out in the frequency domain to find the beneficial parameters by which the maximum vibration reduction can be achieved. The key parameters investigated include the distance from the centre line of SATLCD to the rotational axis of a structure, the ratio of horizontal length to the total length of liquid column, head loss coefficient, and frequency offset ratio. The investigations demonstrate that SATLCD can provide a greater flexibility for its application in practice and achieve a high degree of vibration reduction. The sensitivity of SATLCD to the frequency offset between the damper and structure can be improved by adapting its frequency precisely to the measured structural frequency.

• International Journal of Control, Automation, and Systems
• /
• 제4권6호
• /
• pp.756-762
• /
• 2006

Shape Memory Alloy(SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.704-707
• /
• 1997

In this paper, we present a fuzzy logic based tuner for continuous on-line tuning of PID controllers. The essential idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a singler parameter .alpha., then to use an on line fuzzy logic to self-tune the parameter. The adaptive scaling makes the controller robust against large variations in parametric and dynamics uncertainties in the plant model. New self-tuning controller has the ability to decide when to use PI or PID control by extracting process dynamics from relay experiments. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with nonminimum phase processes.

• 전자공학회논문지B
• /
• 제32B권8호
• /
• pp.1119-1126
• /
• 1995

The construction of rule-base for a nonlinear time-varying system, becomes much more complicated because of model uncertainty and parameter variations. Furthemore, FLC does not have an ability of adjusting rule- base in responding to some sudden changes of control environments. To cope with these problems, an auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), which is known to be very effective in the optimization problem, will be proposed. The tuning of the proposed system is performed by two tuning processes(the course tuning process and the fine tuning/adaptive learning process). The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• 한국음향학회:학술대회논문집
• /
• 한국음향학회 1993년도 학술논문발표회 논문집 제12권 1호
• /
• pp.45-49
• /
• 1993

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 2000년도 춘계학술대회논문집
• /
• pp.56-63
• /
• 2000

Abstract - In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

• 한국정밀공학회지
• /
• 제21권10호
• /
• pp.65-77
• /
• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제49권4호
• /
• pp.201-212
• /
• 2000

In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the cast that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1986년도 하계학술대회논문집
• /
• pp.132-135
• /
• 1986

This paper shows that using the multivariable controller reduces the magnitude of fluctuations of the control signals which result improved control of the steam generator outputs. Comparison of the performance of the multivariable weighted adaptive controller(MWAC) with the performance of the existing PI controller and the self_tuning controller/1/, when the system goes through a transient mode, shows that the out-puts stay closer to their set points when they are controlled by the adaptive controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2002년도 ICCAS
• /
• pp.39.2-39
• /
• 2002

This paper presents adaptive add-on control algorithms for theconventional mode of operation of MEMS z-axis gyroscopes. This scheme is realized by adding an outer loop to a conventional force-balancing scheme that includes a parameter estimation algorithm. The parameter adaptation algorithm estimates the angular rate, identifies and compensates the quadrature error, and may permit on-line automatic mode tuning. The convergence and resolution analysis show that the proposed adaptive add-on control scheme prevents the angular rate estimate from being contaminated by the quadrature error, while keeping ideal resolution performance of a conventional force-balancing scheme.