• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.556-562
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• 2002

This paper studies the identification of a combustion model, which is used to design a linear controller of a steam generation quantity and harmful exhaust gases of a Refuse Incineration Plant(RIP). Even though the RIP has strong nonlinearities and complexities, it is identified as a MIMO parametric ARX model from experimental input-output data sets. Unknown model parameters are decided from experimental input-output data sets, using system identification algorithm based on Instrumental Variables(IV) method. It is shown that the identified model well approximates the input-output combustion characteristics.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.2 s.308
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• pp.1-10
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• 2006

This paper is concerned with $H_2$ control design for active vibration control of a plate vibration system. We construct a plate vibration system with a plate, PZT ceramics actuators and sensors. The plate titration system is MIMO system and its transfer matrix is obtained by system identification experiments. We design a $H_2$ controller using the state space model obtained from system identification. Effectiveness and performance of the designed controller are verified by both simulation and experiment results.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.142-155
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• 2000

A MIMO model reference control scheme incorporating the variable structure theory for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of continuous-time nonlinear dynamics with known or unknown uncertainties. The scheme employs an neural network to identify the plant systems, where the neural network estimates the nonlinear dynamics of the plant. By the Lyapunov direct method, the algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed and it is not necessary to know the exact structure of the system. With the resulting identification model which contains the neural networks, it does not need higher degrees of freedom vehicle model than 3 degree of freedom model. Th proposed scheme is applied to the active four wheel system and shows the validity is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the reduction of yaw rate overshoot of a typical mid-size car improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response and smaller side angle than the 2WS case.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.364-369
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• 2007

A system heat pump provides the benefits of comfort, energy conservation and easy maintenance. Recently, the system heat pump has been employed in small and medium-sized buildings. However, the performance data and control algorithm for system heat pump are limited in literature due to complicated system parameters and operating conditions. In the present study, the performance of a system heat pump with two indoor unit is measured by varying indoor loads, EEV opening, and compressor speed. In addition, the integral optimum regulator which includes MIMO control algorithm is proposed. The capacity modulation and optimum capacity for each indoor unit can be adjusted by utilizing the EEVs opening and compressor speed. The proposed scheme shows appropriate control performance at test conditions.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.3
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• pp.354-362
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• 2000

This paper identifies a discrete-time linear combustion model of Refuse Incineration Plant(RIP) which characterizes steam generation quantity, where the RIP is considered as a MIMO system with thirteen-inputs and one-output. The structure of RIP model is described as an ARX model which are analytically obtained from the combustion dynamics. Furthermore, using the Instrumental Variable(IV) identification algorithm, model structure and unknown parameters are identified from experimental input-output data sets, In result, it is shown that the identified ARX model well approximates the input-output combustion characteristics given by experimental data sets.

• Journal of Power System Engineering
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• v.5 no.4
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• pp.53-60
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• 2001

This paper considers a modeling for the MIMO magnetic bearing system. The rotor is flexible and has a complex shape. To obtain the nominal plant transfer functions, we perform a numerical analysis by using the finite element method(F.E.M.) for the rotor's dynamics, and make a nominal model by reducing the modes from the results. And, we have experimented on the frequency response by a closed-loop identification method, and compared it with the simulation's result on the closed-loop control system.

• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.486-491
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• 2008

This paper describes a model identification method that has been applied to a commercial 12-inch RTP (rapid thermal processing) equipment with an ultimate aim to develop a high-performance advanced controller. Seven thermocouples are attached on the wafer surface and twelve tungsten-halogen lamp groups are used to heat up the wafer. To obtain a MIMO balanced state space model, multiple SIMO (single-input multiple-output) identification with highorder ARX models have been conducted and the resulting models have been combined, transformed and reduced to a MIMO balanced state space model through a balanced truncation technique. The identification experiments were designed to minimize the wafer warpage and an output linearization block has been proposed for compensation of the nonlinearity from the radiation-dominant heat transfer. As a result from the identification at around 600, 700, and $800^{\circ}C$, respectively, it was found that $y=T(K)^2$ and the state dimension of 80-100 are most desirable. With this choice the root-mean-square value of the one-step-ahead temperature prediction error was found to be in the range of 0.125-0.135 K.

• Journal of KSNVE
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• v.10 no.6
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• pp.1048-1058
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• 2000

Thipaper presents a methodology to suppress the vibration of thin rectangular plate clamped all edges using piezo-ceramic material as actuators and sensors. Dynamic characteristics of the structure bonded with distributed actuators/sensors are identified by the Multi-Input Multi-Output (MIMO) frequency domain modeling technique based on the experimental data. Hybrid control scheme is adopted and feedback controller is designed by LQG(Linear Quadratic Gaussian). Feedforward controller is adapted by multiple filtered -$x$ LMS(least mean square) algorithm. Experiment result demonstrates the effective reduction of the vibration label for both the transient and persistent external disturbances.

• Journal of Ocean Engineering and Technology
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• v.10 no.1
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• pp.108-118
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• 1996

This paper presents automatic reentry of a deepsea reser by adaptive control. Reentry is one of the major pro blems regarding a deepsea riser. In the reentry operation, the lower end of riser must be accurately positioned over the tarket point on the seabed. But the deepsea riser shows complex elastic response due to flexibility and nonlinearity of the riser dynamics and the required positioning accuracy is high. Moreover, elastic deformation must by controlled for securing structural integrity. In adaptive control, uncertainly known parameters like added mass and drag coefficient in the riser dynamics are identified and control forces at the floating body and the riser are calculated simultaneously. An Adaptive algorithm for MIMO linear discrete time system without requiring a persistent excitation is adopted in this study. The effectiveness of adaptive control logic is tested by numerical simulation and model experiment. The designed control system shows good overall performances, so that the present study can be applied to the control of the deepsea riser.

• Advances in robotics research
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• v.2 no.1
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• pp.99-112
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• 2018

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.