• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.54-64
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• 1997

In this paper, a method of dynamic modeling and a dynamic control of a mobile robot are presented to show the superiority of the dynamic control comparing to the PD control. This dynamic model is derived from the cartesian coordinates using lagrange equations. Based upon the derived dynamic model, we implemented the dynamic control of the mobile robot using the computed torque method. Time varying non-linear friction terms are not incroporated in this dynamic model. Instead, those are considered as disturbances. This uncertainty in dynamic model of mobile robot is compensated by the outer loop controller using PD algorithm. The validity of this model and the control algorithm are confirmed through the experiments, where the dynamic control algorithm demonstrated robust velocity tracking performance against the unmodeled non-linear frictions. The superiority of this algorithm is demonstrated by comparing to classical PD control algorithm.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.4
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• pp.730-734
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• 2013

The dynamic simulation of machine tools and motion control systems has been widely used for optimization, design verification, control design, etc. There are three main streams in dynamic simulation: structural dynamic analysis based onthe finite element method, dynamic motion analysis based on equations of motion, and control system analysis based on transfer functions. Generally, one of these dynamic simulation methods is chosen and employed for specific purposes. In this study, an integrated dynamic simulation is introduced, in which the structure, motion, and control dynamics are combined together. Commercially well-known software is used in the integrated dynamic simulation: ANSYS, ADAMS, and Matlab/Simulink. Using the integrated dynamic simulation, the dynamics of a magnetic bearing stage is analyzed and the causes of oscillation and noise are identified. A controller design for suppressing a flexible dynamic mode is carried out and verified through the integrated dynamic simulation.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.1008-1020
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• 2018

In this paper, the dynamic compliance and its compensation control of the force control system on the highly integrated valve-controlled cylinder (HIVC), the joint driver of the hydraulic drive legged robot, is researched. During the robot motion process, the outer loop dynamic compliance control is applied on the base of hydraulic control inner loop and most inner loop control are the force or torque closed loop control. While the dynamic compliance control effectiveness of outer loop can be affected by the inner loop self-dynamic-compliance. Based on this problem, the dynamic compliance series composition theory of HIVC force control system as well as the analysis of its self-dynamic-compliance is proposed. And then the paper comes up with the compliance-enhanced control, which is a compound compensation control method of dynamic compliance with multiple series branches. Finally, the experiment results indicate that the control method mentioned above can enhance the dynamic compliance of HIVC force control system observably. This provides the compensation control method of inner loop dynamic compliance for the outer loop compliance control requiring the high accuracy and high robustness for the robot.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1950-1955
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• 1991

A fuzzy dynamic learning controller is proposed and applied to control of time delayed, non-linear and unstable chemical processes. The proposed fuzzy dynamic learning controller can self-adjust its fuzzy control rules using the external dynamic information from the process during on-line control and it can create th,, new fuzzy control rules autonomously using its learning capability from past control trends. The proposed controller shows better performance than the conventional fuzzy logic controller and the fuzzy self organizing controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.7
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• pp.706-717
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• 1991

In order to remove the assumption of full state availability which is one of the major difficulties with the practical realization of variable structure control systems,a new switching function with a dynamic structure is proposed. And the control performances of the output feedback variable structure control systems with the dynamic switching function are evaluated through simulation studies. The proposed dynamic switching function is driven by small number of measured output and input variables while conventional static switching function requires full state information. Therefore, the proposition of the dynamic swiching function makes practical implementation of output feedback variable structure control scheme possible for the systems with unmeasurable state variables, high order systems and large scale systems that the conventional variable structure control schemes with static switching function cannot be applied. In the variable structure control systems with the dynamic switching function, desired control performance can be guaranteed by proper choice of design parameters such as poles of switching function dynamic equation and switching control gains even though small number of measured output and input variables are provided as shown in simulation resuls.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.280-285
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• 1991

Neural network control has many innovative potentials for fast, accurate and intelligent adaptive control. In this paper, a learning control architecture for the dynamic control of a robot manipulator is developed using inverse dynamic neurocontroller and linear neurocontroher. The inverse dynamic neurocontrouer consists of a MLP (multi-layer perceptron) and the linear neurocontroller consists of SLPs (single layer perceptron). Compared with the previous type of neurocontroller which is using an inverse dynamic neurocontroller and a fixed PD gain controller, proposed architecture shows the superior performance over the previous type of neurocontroller because linear neurocontroller can adapt its gain according to the applied task. This superior performance is tested and verified through the control of PUMA 560. Without any knowledge on the dynamic model, its parameters of a robot , (The robot is treated as a complete black box), the neurocontroller, through practice, gradually and implicitly learns the robot's dynamic properties which is essential for fast and accurate control.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.636-639
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• 1997

In this paper, a dynamic control scheme is proposed which not only compensates for the lateral dynamics and longitudinal dynamics but also deal with the yaw motion dynamics. Using the dynamic control technique, adaptive and learning algorithm together, the proposed controller is not only robust to disturbance and parameter uncertainties but also can learn the inverse dynamics model in steady state. Based on the proposed dynamic control scheme, a dynamic vehicle simulator is contructed to design and test various control techniques for 4-wheel steering vehicles.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.181-188
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• 2007

This paper presents a torque control method of a hydraulic actuation system for measuring the dynamic stiffness of missile fin actuators. We propose a new control technique called Dual Dynamic Torque Feedback Control(DDTFC), which improves the stability of the torque control system and enables fast tracking of torque command. The developed control scheme is derived from the physical understanding based on mathematical modelling and analysis. The dynamics of hydraulic torque control servo-system is unravelled via physics-based modelling and nonparametric system identification. In order to verify the effectiveness of the method, the experiment is carried out with a test equipment for measuring the dynamic stiffness. The experiment and simulation results show that DDTFC gives stability improvement.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.53-60
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• 2007

This paper presents a robust nonlinear autopilot design method based on dynamic inversion and PI(Proportional-Integral) control law. The new controller structure which is different from previous work is composed of classical linear PI control law and nonlinear fast dynamic inversion. A pitch axis model of highly maneuverable missiles and a linearized model for designing Pl controller are presented. The performance of proposed method is illustrated via nonlinear simulations including aerodynamic uncertainties and actuator dynamics.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.11
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• pp.994-1003
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• 2000

Control algorithms for the absorption air conditioning system may be developed by suing dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help the development of effective control algorithms for the system. In this study, a dynamic simulation program for the absorption air conditioning system was developed. Dynamic models for an absorption chiller, a cooling tower, an air handling unit, a boiler, a three way valve, a controller, and a duct were developed and programed. Control algorithms for the absorption chiller, the cooling tower, and the air handling unit were selected, and analyzed to show the effectiveness of dynamic models. From the simulation results, it may be concluded that this simulation program may be effectively used for the development of optimal control algorithms of the absorption air conditioning system.