• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.3
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• pp.205-212
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• 2008

This paper describes the application of an inverse building model to a calibrated forward building model using EnergyPlus program. Typically, inverse models are trained using measured data. However, in this study, an inverse building model was trained using data generated by an EnergyPlus model for an actual office building. The EnergyPlus model was calibrated using field data for the building. A training data set for a month of July was generated from the EnergyPlus model to train the inverse model. Cooling load prediction of the trained inverse model was tested using another data set from the EnergyPlus model for a month of August. Predicted cooling loads showed good agreement with cooling loads from the EnergyPlus model with root-mean square errors of 4.11%. In addition, different control strategies with dynamic cooling setpoint variation were simulated using the inverse model. Peak cooling loads and daily cooling loads were compared for the dynamic simulation.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.301-307
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• 2004

An inverse dynamic model of lower limbs is presented to calculate joint moments during gait. The model is composed of 4 segments with 3 translational joints and 12 revolute joints. The inverse dynamic method is based on Newton-Euler formalism. Kinematic data are obtained from 3 dimensional trajectories of markers collected by a motion analysis system. External forces applied on the foot are measured synchronously using force plate. The use of developed model makes it possible to calculate joint moments for variation of parameters.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2188-2190
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• 2004

This paper presents an implementation of power system stabilizer using inverse dynamic neuro controller. Traditionally, mutilayer neural network is used for a universal approximator and applied to a system as a neuro-controller. In this case, at least two neural networks are used and continuous tuning of neuro-controller is required. Moreover, training of neural network is required considering all possible disturbances, which is impractical in real situation. In this paper, Taylor Model Based Inverse Dynamic Neuro Model (TMBIDNM) is introduced to avoid this problem. Inverse Dynamic Neuro Controller (IDNC) consists of TMBIDNM and Error Reduction Neuro Model (ERNM). Once the TMBIDNM is trained, it does not require retuning for cases with other types of disturbances. The controller is tested for one machine and infinite-bus power system for various operating conditions.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.7 no.1
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• pp.21-27
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• 2013

Manual wheelchair propulsion can lead to pain and injuries of users due to mechanical inefficiency of wheelchair propulsion motion. The kinetic analysis of the upper limbs during manual wheelchair propulsion needs to be studied. A two dimensional inverse dynamic model of upper limbs was developed to compute the joint torque during manual wheelchair propulsion. The model was composed of three segments corresponding to upper arm, lower arm and hand. These segments connected in series by revolute joints constitute open chain mechanism in sagittal plane. The inverse dynamic method is based on Newton-Euler formalism. The model was applied to data collected in experiments. Kinematic data of upper limbs during wheelchair propulsion were obtained from three dimensional trajectories of markers collected by a motion capture system. Kinetic data as external forces applied on the hand were obtained from a dynamometer. The joint rotation angles and joint torques were computed using the inverse dynamic model. The developed model is for upper limbs biomechanics and can easily be extended to three dimensional dynamic model.

• Journal of Mechanical Science and Technology
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• v.16 no.1
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• pp.13-23
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• 2002

This paper presents inverse kinematic and dynamic analyses of HexaSlide type six degree-of-freedom parallel manipulators. The HexaSlide type parallel manipulators (HSM) can be characterized as an architecture with constant link lengths that are attached to moving sliders on the ground and to a mobile platform. In the inverse kinematic analyses, the slider and link motion (position, velocity, and acceleration) is computed given the desired mobile platform motion. Based on the inverse kinematic analysis, in order to compute the required actuator forces given the desired platform motion, inverse dynamic equations of motion of a parallel manipulator is derived by the Newton-Euler approach. In this derivation, the joint friction as well as all link inertia are included. Relative importance of the link inertia and joint frictions on the computed torque is investigated by computer simulations. It is expected that the inverse kinematic and dynamic equations can be used in the computed torque control and model-based adaptive control strategies.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2000.05a
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• pp.6-10
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• 2000

In this paper a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a low-pass prefilter the inverse dynamic model of a system and the PI controller. The low-pass prefilter prevents high frequency effects from the inverse dynamic model. The model is characterized by a nonlinear friction model. The PI controller regulates the error between the set-point and the system output which is caused by modeling error disturbances and variations f parameters. The parameters of the model and the PI controller are optimized offlinely by genetic algorithm. The experimental results on a DC motor system illustrate the performance of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1972-1977
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• 2005

In this work, an inverse dynamic control method is developed to enhance tracking performance of industrial robots, which effectively deal with the nonlinear dynamic interferential forces. In general, the DFF (Dynamic Feed-Forward) controller and the CTM (Computed-Torque Method) controller are used for dynamic control for industrial robots. We study on the practical issues for implementing these inverse dynamic controllers via simulations and experiments. We develop the dynamic models in two different ways. One is a model designed through Newton-Euler method for real time computation and the other is a model designed through SimMechanics for evaluating the developed controller via simulations. We evaluate the nominal performance and robustness of the controller via simulations and experiments using serial 4-DOF HyRoHILS (Hyundai Robot Hardware-In-the-Loop Simulation) system. The results show that the inverse dynamic controller is effective and practically useful for a real control structure.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.5
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• pp.97-102
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• 2000

In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a prefilter, the inverse dynamic model of a system and the PI controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system in characterized by a nonlinear equation with coulomb friction. The PI controller regulates the error between the set-point and the system output which may be caused by modeling error, variations of parameters and disturbances. The output which may be caused by modeling error, variations of parameters and disturbances. The parameters of the model and the PI controller are adjusted offlinely by a genetic algorithm. An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.138-138
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• 2000

In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a prefilter, the inverse dynamic model of a system and a fuzzy logic controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system is characterized by a nonlinear equation with coulomb friction. The fuzzy logic controller regulates the error between the set-point and the system output which may be caused by disturbances and it simultaneously traces the change o( the reference input. The parameters of the model are estimated by a genetic a]gorithm. An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.2
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• pp.262-268
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• 2019

Previous dynamic models of hysteresis motor use an extended induction machine equivalent circuit or somewhat different equivalent circuit with conventional one, which makes unsatisfiable results. In this paper, the hysteresis dynamic characteristics of the motor rotor are analyzed using the inverse Preisach model and the hysteresis motor equivalent circuit considering eddy current effect. The hysteresis loop for the rotor ring is analyzed under full-load voltage source static state. The calculated hysteresis loop is then approximated to an ellipse for simplicity of dynamic computation. The permeability and delay angle of the elliptic loop apply to the dynamic analysis model. As a result, it is possible to dynamically analyze the hysteresis motor according to the applied voltage and the rotor material. With this method, the motor speed, generated torque, load angle, rotor current as well as synchronous entry time, hunting effect can be calculated.