• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.931-938
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• 2008

In this paper, a novel localization algorithm robust to the unmodeled systematic odometry errors is proposed for low-cost non-holonomic mobile robots. It is well known that the most pose estimators using odometry measurements cannot avoid the performance degradation due to the dead-reckoning of systematic odometry errors. As a remedy for this problem, we tty to reflect the wheelbase error in the robot motion model as a parametric uncertainty. Applying the Krein space estimation theory for the discrete-time uncertain nonlinear motion model results in the extended robust Kalman filter. This idea comes from the fact that systematic odometry errors might be regarded as the parametric uncertainties satisfying the sum quadratic constrains (SQCs). The advantage of the proposed methodology is that it has the same recursive structure as the conventional extended Kalman filter, which makes our scheme suitable for real-time applications. Moreover, it guarantees the satisfactoty localization performance even in the presence of wheelbase uncertainty which is hard to model or estimate but often arises from real driving environments. The computer simulations will be given to demonstrate the robustness of the suggested localization algorithm.

• Journal of Power System Engineering
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• v.20 no.2
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• pp.58-65
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• 2016

Lately, tugboats are widely used to maneuver vessels by pushing or towing them where tugboats use rope. In order to correctly control the motion of tugboat and towed vessel, the dynamics of the towline would be well identified. In real application environment, the towing rope length changes and the towing load is not constant due to the various sizes of towed vessel. And there are many ropes made by many types of materials. It means that it is not easy to obtain rope dynamics, such that it is too difficult to satisfy the given control purpose by designing control system. Thus real time identification or adaptive control system design method may be a solution. However it is necessary to secure sufficient information about rope dynamics to obtain desirable control performance. In this paper, the authors try to have several rope dynamic models by changing the rope length to consider real application conditions. Among them, a representative model is selected and the others are considered as uncertain models which are considered in control system design. The authors design a robust control to cope with strong uncertain and nonlinear property included in the real plant. The designed control system based on robust control framework is evaluated by simulation.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.387-396
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• 2005

The Rotational/Translational Actuator (RTAC) benchmark problem considers a fourth-order dynamical system involving the nonlinear interaction of a translational oscillator and an eccentric rotational proof mass. This problem has been posed to investigate the utility of a rotational actuator for stabilizing translational motion. In order to experimentally implement any of the model-based controllers proposed in the literature, the values of model parameters are required which are generally difficult to determine rigorously. In this paper, an approach to the least-squares estimation of the parameters of a system is formulated and practically applied to the RTAC system. On the other hand, this paper shows how to model a nonlinear system as a linear uncertain system via nonparametric system identification, in order to provide the information required for linear robust $H_\infty$ control design. This method is also applied to the RTAC system, which demonstrates severe nonlinearities, due to the coupling from the rotational motion to the translational motion. Experimental results confirm that this approach can effectively condense the whole nonlinearities, uncertainties, and disturbances within the system into a favorable perturbation block.

• Journal of Ocean Engineering and Technology
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• v.22 no.4
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• pp.90-96
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• 2008

In general, the swing motions of a crane are controlled and suppressed by controlling the trolley motion. In many of our previous studies, we suggested a new type of anti-sway control system for a crane. In this proposed control system, a small auxiliary mass (moving-mass) is installed on the spreader and moving this auxiliary mass controls tire swing motion. The actuator reaction against the auxiliary mass applies inertial control forces to the container in order to reduce the swing motion in the desired manner. However, measuring systems based on a laser sensor or other means are not veryuseful in real-worldapplications. So, in this paper, animage sensor is used to measure the motions of the spreader and the measured data are fed back to the controller in real time. The applied image processing technique is a kind of robust template matching method called Vector Code Correlation (VCC), which was devised to consider real environmental conditions. The H $\infty$ based control technique is applied to suppress the swing motion of the crane. Experimental results showed that the proposed measurement and control system based on an image sensor is useful and robust to disturbances.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.20-27
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• 1994

This paper presents a controller design to coordinate a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme is applied. Since parameters of the robot manipulators such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters works as a disturbance force. To identify the unknown parameters, an improved adaptive control algorithm is directly derived from a chosen Lyapunov's function candidate based on the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing forces coming from the difference between the actual and the estimated system parameters. Numerical examples are shown using three degree-of-freedom planar arm.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.649-651
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• 2015

This paper describes a robust adaptive sliding mode control (RASMC) for torque ripple minimization of switched reluctance motor (SRM) using it in automotive application. The objective is to control effort smoothness while the system is under perturbations by unstructured uncertainties, unknown parameters and external disturbances. The control algorithm employs an adaptive approach to remove the need for prior knowledge within the bound of perturbations. This is suitable for tackling the chattering problem in the sliding motion of sliding mode control method. The algorithm then incorporates modifications in order to build a chattering-free modified robust adaptive sliding mode control using Lyapunov stability theory.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.23-31
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• 1997

The sway control problem of pendulum motion of a container hanging on a Portainer Crane, which transports containers from a container ship to trucks, is considered in the paper. The equations of motion are obtained through the Lagrange mechanics and simplified for control purposes. Considering that the fast traveling of trolley and no residual swing motion of the container at the end of acceleration and deceleration are crucial for quick transportation, several velocity patterns of trolley movement including the time-optimal control are investigated. Incorporating the change of rope length, a reference swing trajectory is introduced in the control loop and the error signal between the reference sway angle and the measured sway angle is feedbacked. Proposed control strategy is shown to be robust to disturbances like winds and initial sway motion.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1780-1787
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• 2014

Arterial oxygen saturation ($SpO_2$) monitoring for newborns requires special attention in neonatal intensive care units (NICUs). Newborns have very low photo-plethysmogram (PPG) amplitudes and their body movements are difficult to contain. Hardware design and its associated signal processing algorithms should be robust enough so that faulty measurements can be avoided. In this study, improved designs were implemented to deal with low perfusion, motion artifact, and the influence of ambient light. Dynamic range was increased by using different LED intensities and a feedback system. To minimize the effects of motion artifact and to discard other unqualified data, four additional algorithms were used, which were based on dual-trace detection, continuity of DC level, morphology of PPG, and simultaneity check of $SpO_2$. Our $SpO_2$ system was tested with newborns with normal respiration in the NICU. Our system provided fast, real-time responses and 100% artifact detection was accomplished under 84% of $SpO_2$.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.