• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.11
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• pp.1819-1826
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• 1997

Direct-drive robots are suitable to the position and force control with high accuracy, but it is difficult to design a controller because of the system's nonlinearity and link-interactions. This paper is concerned with the study of the force control of direct-drive robots. The proposed algorithm consists of feedback controllers and a neural network. After the completion of learning, the output of feedback controller is nearly equal to zero, and the neural network controller plays an important role in the control system. Therefore, the optimum retuning of parameters of feedback controllers is unnecessary. In other words, the proposed algorithm does not require any knowledge of the controlled system in advance. The effectiveness of the proposed algorithm is demonstrated by the experiment on the force control of the parallelogram link-type direct-drive robot.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.144-155
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• 2004

This paper addresses the issue of position control of a chain of multiple mass-spring-damper (CMMSD) units which can be found in many physical systems. The dynamic model of a CMMSD system with any degrees of freedom is expressed in a closed-form for the convenience of the controller design. Backstepping and model reference adaptive control (MRAC) approaches are then used to develop two adaptive output feedback controllers to control the position of a CMMSD system. The proposed controllers rely on the measurements of the input (force) and the output (position of the mass unit at the end of the chain) of the system without the knowledge of its parameters and internal states. Simulations are used to verify the effectiveness of the controllers

• Journal of Drive and Control
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• v.10 no.3
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• pp.14-20
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• 2013

In the study, a control strategy using a feedback linearization compensator and a disturbance observer was suggested and applied to the synchronization control of two hydraulic cylinders. The hydraulic system consists of a proportional directional control valve with overlap characteristic near the neutral position, a conventional hydraulic cylinder and an external load. The control performances of the system were verified through numerical simulations. From the simulations, it was ascertained that excellent control performances were obtained with the suggested control strategy.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.38-42
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• 2002

Conditions are discussed for operating a dissymmetric human master-small (or micro) slave system in best (large position gain-small velocity gain) conditions allowing higher operator dexterity when real effects (joint compliance, link flexion delay and transmission distortion) are taken into account. It is shown that position PD feedback law advantage for ideal case no longer holds, and that more complicated feedback law depending on real effects has to be implemented with adapted transmission line. Drawback is slowdown of master slave interaction, suggesting to use more advanced predictive methods for the master and more intelligent control law for the slave.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.185-188
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• 1998

In this paper, we propose a feedback adaptive controller which need not adjustment of the scale factor. Numerical examples are included to illustrate the procedure of a adaptive control and to show the performance of the control system. We can observe that the output of control system, converges toward the reference of response.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4342-4366
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• 2016

Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur'e type system. In the context of delayed Lur'e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.464-473
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• 2006

This paper summarises theoretical and experimental work on the feedback control of sound radiation from honeycomb panels using piezoceramic actuators. It is motivated by the problem of sound transmission in aircraft, specifically the active control of trim panels. Trim panels are generally honeycomb structures designed to meet the design requirement of low weight and high stiffness. They are resiliently-mounted to the fuselage for the passive reduction of noise transmission. Local coupling of the closely-spaced sensor and actuator was observed experimentally and modelled using a single degree of freedom system. The effect of the local coupling was to roll-off the response between the actuator and sensor at high frequencies, so that a feedback control system can have high gain margins. Unfortunately, only relatively poor global performance is then achieved because of localisation of reduction around the actuator. This localisation prompts the investigation of a multichannel active control system. Globalised reduction was predicted using a model of 12 channel direct velocity feedback control. The multichannel system, however, does not appear to yield a significant improvement in the performance because of decreased gain margin.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.653-659
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• 2006

The design of $H_2$-optimal control with regional pole assignment via state feedback in linear time-invariant systems is investigated. The aim is to find a state feedback controller such that the closed-loop system has the desired eigenvalues lying in some desired stable regions and attenuates the disturbance between the output vector and the disturbance vector. Based on a proposed result of parametric eigenstructure assignment via state feedback in linear systems, the considered $H_2$-optimal control problem is changed into a minimization problem with certain constraints, and a simple and effective algorithm is proposed for this considered problem. A numerical example and its simulation results show the simplicity and effectiveness of this proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.260-269
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• 2000

The fuzzy and state-feedback control systems have been applied in various areas from non-linear to linear systems. A Fuzzy controller is endowed with control rules and membership function that are constructed on the knowledge of expert, as like intuition and experience. but It is very difficult to obtain the exact values which are the membership function and consequent parameters. though apply back-propagation algorithm to the system, the convergence time a much. Besides, the state-feedback system is most widely used in industry due to its simple control structure and easily able to design the controller. but it is weak in complex system of higher degree and non-linear. In this paper presents the design of a fuzzy switching mode, it these two controllers work at different operation conditions, the advantages of both controller can be retained and the disadvantages can be removed. Between the Fuzzy and the State-feedback controlles, the good outputs are selected by the switching mode. Moreover it is powerful in complex system of higher degree and non-linear. In these sense compared with the state-feedback controller, the performance of the proposed controller was improvedin the section of linearization.

• Journal of IKEEE
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• v.14 no.3
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• pp.182-189
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• 2010

A new Adaptive neural state-feedback controller for the fully nonaffine pure-feedback nonlinear system are presented in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controller requires no backstepping design procedure. Avoiding backstepping makes the controller structure and stability analysis considerably simple. The proposed controller employs only one neural network to approximate unknown ideal controllers, which highlights the simplicity of the proposed neural controller. Simulation examples demonstrate the efficiency and performance of the proposed approach.