• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.9
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• pp.1376-1385
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• 1993

This paper presents a new dynamic model which is represented by the second order differenatial equation and itcludes the robot arm dynamics as well as the actuator dynamics. The model exhibits excellent performance in the steady state and transient response. In addition the time varing nonlinear and coupled dynamic system has been linearized and decoupled by using nonlinear feedback and linearization method. In this case a pole assignment law is used to improve stability, and the optimal control altorithm is applied to the error equation to minimize the path error. In applying the proposed algorithm to the three joint manipulator with actuators, we obtained very encouraging results.

• Journal of Ocean Engineering and Technology
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• v.23 no.2
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• pp.1-7
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• 2009

This paper presents a sliding mode controller based on Ackermann's formula and applies it to stabilizing a two-wheeled mobile inverted pendulum in equilibrium. The mobile inverted pendulum is a system with an inverted pendulum on a mobile cart. The dynamic modeling of the mobile inverted pendulum was established under the assumptions of a cart with no slip and a pendulum with only planar motion. The proposed sliding mode controller was based upon a class of nonlinear systems whose nonlinear part of the modeling can be linearly parameterized. The sliding surface was obtained in an explicit form using Ackermann's formula, and then a control law was designed from reachability conditions and made the sliding surface attractive to the equilibrium state of the mobile inverted pendulum. The proposed controller was implemented in a Microchip PIC16F877 micro-controller. The developed overall control system is described. The simulation and experimental results are presented to show the effectiveness of the modeling and controller.

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.72-78
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• 2005

This paper describes the design of a robust output-feedback controller for a single-input single-output nonlinear dynamical system with a full relative degree. While all the previous research works on the output-feedback control are based on dynamic observers, a new state estimator which uses the past values of the measurable system output is proposed. We name it backward-difference state estimator since the derivatives of the output are estimated simply by backward difference of the present and past values of the output. The disturbance generated due to the error between the estimated and real state variables is compensated using an additional robustifying control law whose gain is tuned adaptively. Overall control system guarantees that the tracking error is asymptotically convergent and that all signals involved are uniformly bounded. Theoretical results are illustrated through a simulation example of inverted pendulum.

• International Journal of Automotive Technology
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• v.4 no.4
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• pp.181-191
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• 2003

Since the nonlinearity and uncertainties which inherently exist in vehicle system need to be considered in active suspension control law design, this paper proposes a new control strategy for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a genetic algorithm (GA) based self-tuning PID controller and a fuzzy logic controller in two loops. In the control scheme, the PID controller is used to minimize vehicle body vertical acceleration, the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors. In order to improve the adaptability to the changes of plant parameters, based on the defined objectives, a genetic algorithm is introduced to tune the parameters of PID controller, the scaling factors, the gain values and the membership functions of fuzzy logic controller on-line. Taking a four degree-of-freedom nonlinear vehicle model as example, the proposed control scheme is applied and the simulations are carried out in different road disturbance input conditions. Simulation results show that the present control scheme is very effective in reducing peak values of vehicle body accelerations, especially within the most sensitive frequency range of human response, and in attenuating the excessive dynamic tire load to enhance road holding performance. The stability and adaptability are also showed even when the system is subject to severe road conditions, such as a pothole, an obstacle or a step input. Compared with conventional passive suspensions and the active vehicle suspension systems by using, e.g., linear fuzzy logic control, the combined PID and fuzzy control without parameters self-tuning, the new proposed control system with GA-based self-learning ability can improve vehicle ride comfort performance significantly and offer better system robustness.

• Journal of Mechanical Science and Technology
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• v.18 no.9
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• pp.1519-1528
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• 2004

Atmospheric Re-Entry guidance is divided as longitudinal and lateral. This paper proposes a longitudinal reference trajectory and control law using the inverse dynamics method with pseudospectral Legendre method. Application of this method into Re-Entry problem forces a power of calculation time-reduction due to unnecessary of integration or any iteration as well as sufficient accuracy convergence. The used guidance scheme is time-to-go.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.1
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• pp.118-128
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• 2006

This paper deals with auto-landing guidance system design applicable to Smart UAV(Unmanned Aerial Vehicle). The proposed guidance law generates horizontal position, velocity and altitude commands in the longitudinal channel and heading angle command in the lateral channel to track a predetermined trajectory for automatic landing. The longitudinal guidance commands are derived from an approximated dynamic equations in vertical plane. These longitudinal guidance commands are appropriately distributed to each control input as the flight mode of Smart UAV is changed. The concept of VOR(VHF Omni-directional Range) guidance system is applied to generate the required heading angle commands to eliminate the lateral deviation from the desired trajectory. The performance of the proposed guidance system for Smart UAV is evaluated using the nonlinear simulation. Simulation results show that the proposed guidance system for auto- landing provides good tracking performance along the predetermined landing trajectory.

• Journal of Power System Engineering
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• v.14 no.6
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• pp.35-40
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• 2010

This article deals with the numerical analysis results of stiffness of diaphragm spring used in the clutch of a manual transmission. In order to investigate the relationship of the force and displacement in a diaphragm spring, we have established a numerical model of diaphragm spring using a well-known analytic model of Belleville spring and a cantilever beam model for the finger part of diaphragm spring. Using the stress and strain relations of Belleville spring and cantilever beam, we propose the analytic equation of motion of diaphragm spring for the use of a clutch automated actuator in an automated manual transmission. The proposed analytic model represents the typical dynamic characteristics of diaphragm spring along with the release bearing travel. And it is characterized in a closed-form equation, therefore it can be used for the further study of development of actuator and control law of clutch automating mechanism.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.869-879
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• 1995

The new field of learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this task. The simplest forms of learning control are based on the same concept as integral control, but operating in the domain of the repetitions of the task. In the previous paper, I had studied the use of such controllers in a decentralized system, such as a robot with the controller for each link acting independently. The basic result of the paper is to show that stability of the learning controllers for all subsystems when the coupling between subsystems is turned off, assures stability of the decentralized learning in the coupled system, provided that the sample time in the digital learning controller is sufficiently short. In this paper, we present two examples. The first illustrates the effect of coupling between subsystems in the system dynamics, and the second studies the application of decentralized learning control to robot problems. The latter example illustrates the application of decentralized learning control to nonlinear systems, and also studies the effect of the coupling between subsystems introduced in the input matrix by the discretization of the system equations. The conclusion is that for sufficiently small learning gain, and sufficiently small sample time, the simple learning control law based on integral control applied to each robot axis will produce zero tracking error in spite o the dynamic coupling in the robot equations. Of course, the results of this paper have much more general application than just to the robotics tracking problem. Convergence in decentralized systems is seen to depend only on the input and output matrices, provided the sample time is suffiently small.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.643-651
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• 2020

A capsule train runs inside a sub-vacuum tube and can reach very high speed due to the low air resistance. A capsule train uses a superconducting electrodynamic suspension (SC-EDS) method for levitation, which allows for a large levitation gap and does not require gap control. However, SC-EDS has inherent characteristics such as the large gap variation and a small damping effect in the levitation force, which can degrade the running stability and ride comfort. To overcome this, a stability improvement device should be designed and applied based on dynamic analysis. In this study, a 1/10 small-scale testbed was developed to replicate the dynamic characteristics of a capsule train and investigate the performance of stability improvement devices. The testbed is composed of a 6-degree-of-freedom Stewart platform for the realization of bogie motion, a secondary suspension with a running stabilization device, and a carbody. Based on the dynamic similarity law proposed by Jaschinski, the small-scale testbed was manufactured, and a bogie motion algorithm was applied with the consideration of guideway irregularity and levitation stiffness. The experimental results from the testbed were compared with simulation results to investigate the performance of the testbed.