• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.669-674
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• 1989

Robot manipulators are highly coupled nonlinear systems and their motions are influenced by uncertain dynamics. In this paper a design methodology which is called model feedback control system or plant model control scheme is presented for the purpose of reducing the influence of the uncertain dynamics. This control system is applied to the trajectly control of the directly drived robot. Theoretically and experimentally performances resulting from use of this control scheme show that the influences of the uncertain dynamics are reduced obviously.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.902-911
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• 2012

This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.924-930
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• 1989

This paper presents the design of simple robust controller for a class of uncertain multivariable systems. We introduce switching dynamics instead of switching logics unlike variable structure control scheme. Also, we can construct the continuous control law from this switching dynamics and consequently remove the chattering motion. The dynamic equations of the range-space of a switching surface matrix C and uniform ultimate boundedness in the presence of parameter uncertainties are described mathematically.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.265-271
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• 2005

Randomness exists in engineering. Tolerance, assemble-error, environment temperature and wear make the parameters of a mechanical system uncertain. So the behavior or response of the mechanical system is uncertain. In this paper, the uncertain parameters are treated as random variables. So if the probability distribution of a random parameter is known, the simulation of mechanical multibody dynamics can be made by Monte-Carlo method. Thus multibody dynamics simulation results can be obtained in statistics. A new concept called functional reliability is put forward in this paper, which can be defined as the probability of the dynamic parameters(such as position, orientation, velocity, acceleration etc.) of the key parts of a mechanical multibody system belong to their tolerance values. A flexible mechanical arm with random parameters is studied in this paper. The length, width, thickness and density of the flexible arm are treated as random variables and Gaussian distribution is used with given mean and variance. Computer code is developed based on the dynamic model and Monte-Carlo method to simulate the dynamic behavior of the flexible arm. At the same time the end effector's locating reliability is calculated with circular tolerance area. The theory and method presented in this paper are applicable on the dynamics modeling of general multibody systems.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.8
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• pp.1203-1211
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• 2009

The dynamics of underwater vehicles can be greatly influenced by the dynamics of the vehicle thrusters. The control of the state of the hovering or very slow motion of the underwater vehicle is most important for automatic docking or control of the manipulator of the vehicle. The dynamics of the thruster based on the electric motor is nonlinear and has uncertain parameters. Since the dynamics of the vehicle coupled with the dynamics of the thruster is nonlinear and has uncertain parameters, a robust control is very effective for a desired motion tracking of the uncertain and nonlinear vehicle. In this paper a study was performed on the robust control scheme of the very slow motion or hovering motion of the underwater vehicle actuated by the electric motor. Also, a concurrent control on the state of the vehicle with nonlinearity and uncertain parameters was performed. A sliding mode control algorithm out of robust controllers was designed and applied, which compensates the nonlinear forces and uncertain parameters of the vehicle and actuator. Through a computer simulation, the proposed control scheme was compared with a linear PD controller and its superior performance was validated.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.54-67
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• 2003

In this paper, a novel estimation technique for a robust adaptive control scheme is presented for a class of uncertain nonlinear systems with a general set of uncertainty. For a class of introduced more extended semi-strict feedback forms which generalize the systems studied in recent years, a novel estimation technique is proposed to estimate the states of the fully nonlinear unmodeled dynamics without stringent conditions. With the introduction of powerful functions, the estimation error can be tuned to a desired small region around the origin via the estimator parameters. In addition, with some effective functions, a modified adaptive backstepping for dynamic uncertainties is presented to drive the output to an arbitrarily small region around the origin by an appropriate choice of the design parameters. With our proposed schemes, we can remove or relax the assumptions of the existing results.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1238-1245
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• 2014

This paper proposes an RBFN-based adaptive tracking controller for an electrically driven mobile robot with parametric uncertainties and external disturbances. A mobile robot model considered in this paper includes all models of the robot body and actuators with uncertain kinematic and dynamic parameters, and uncertain frictions and external disturbances. The proposed controller consists of an RBFN(Radial Basis Function Network) and a robust adaptive controller. The presented RBFN is used to approximate unknown nonlinear robot dynamic functions. The proposed controller is adjusted by the adaptation laws obtained through the Lyapunov stability analysis. The proposed control scheme does not a priori need the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. Also, nominal parameter values are not required in the controller. The global stability of the closed-loop robot control system is guaranteed using the Lyapunov stability theory. Simulation results show the validity and robustness of the proposed control scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.117-127
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• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently, fuzzy controllers are becoming quite popular for robust control due to its potential of dealing with uncertain systems. Thus in this paper we design an adaptive fuzzy controller based on an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Also this paper proposes a fuzzy system that estimates the upper bound of uncertain term in the system dynamics to guarantee the Lyapunov stability. Simulation results show that good performance is achieved by the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.225-225
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• 2000

We propose the hybrid robust controller for TDC(Time Delay Control) and SMC(Sliding Mode Control) method. TDC and SMC deal with the time-varying system parameters, unknown dynamics and unexpected disturbance. This controller is applied to follow the desired reference model for the uncertain time-varying overhead crane. The control performance is evaluated through simulation. The theoretical results indicate That the proposed controller shows excellent performance to an overhead crane with the uncertain time-varying parameters and disturbance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2519-2526
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• 2002

A disturbance observer-based vehicle stability controller is proposed in this paper. The lumped disturbance to the vehicle yaw rate dynamics caused by the uncertain factors such as uncertain tire forces and parameters is estimated by the disturbance observer, which is utilized by the robust controller to stabilize the lateral dynamics of the vehicle. The dynamics of the hydraulic actuator is incorporated in the vehicle stability controller design using the model reduction technique. Modular control design methodology is adopted to effectively deal with the mismatched uncertainty. Simulation results indicate that the proposed disturbance observer-based vehicle stability controller can achieve the desired reference tracking performance as well as sufficient level of robustness.