• Title/Summary/Keyword: Control law approach

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Robust Stabilization of Nonminimum Phase Nonlinear Systems with Parametric Uncertainty (파라미터 불확실성을 갖는 비최소위상 비선형 시스템의 강인 안정화 제어)

  • Joo, Jin-Man;Choi, Yoon-Ho;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 1997.07b
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    • pp.418-421
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    • 1997
  • A control synthesis scheme is presented for nonlinear single-input-single-output (SISO) systems with parametric uncertainty which have completely unstable zero dynamics. The approach involves the derivation of an input-output linearizing control law which achieves internal stability for a nonlinear minimum phase approximation to the original system using Fliess normal form. A vector of unknown constant parameters is also considered. A Lyapunov-based additional control law is shown to stabilize the full system.

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A Robust Adaptive Friction Control of Robot Manipulators using Sliding Surface (슬라이딩 표면을 이용한 로봇 매니퓰레이터의 강건한 적응 마찰 제어)

  • Bae, Jun-Kyung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.11
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    • pp.2139-2146
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    • 2011
  • In this paper, a robust adaptive controller is proposed for trajectory tracking of robot manipulators with the unknown friction coefficient and bounded disturbance. A new adaptive control law is developed based on sliding mode and derived from the Lyapunov stability analysis. The introduction of a boundary layer solves the problem of chattering. The proposed adaptive controller is globally asymptotically stable and guarantees zero steady state error for joint positions. The estimated friction coefficients can also approach the actual coefficients asymptotically. A simulation example is provided to demonstrate the performance of the proposed algorithm.

Nonlinear Formation Guidance Law with Robust Disturbance Observer

  • Shin, Hyo-Sang;Kim, Tae-Hun;Tahk, Min-Jea;Hwang, Tae-Won
    • International Journal of Aeronautical and Space Sciences
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    • v.10 no.1
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    • pp.30-36
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    • 2009
  • Many formation guidance laws have been proposed for VAV formation flight. Since most autonomous formation flight methods require various active communication links between the vehicles to know motion information of other vehicles, damage to the receiver or the transmitter and communication delay are critical problem to achieve a given formation flight mission. Therefore, in this point of view, the method that does not need an inter-vehicle communication is preferred in the autonomous formation flight. In this paper, we first summarize the formation guidance law without an inter-vehicle communication using feedback linearization and sliding mode control proposed in previous study. We also propose the modified formation guidance law with robust disturbance observer, which can provide significantly better performance than previously mentioned guidance law in case that other vehicles maneuver with large accelerations. The robust disturbance observer can estimate uncertainties generated by acceleration of leader vehicle. By eliminating the uncertainties using the estimated uncertainties, VAVs are able to achieve the tight formation flight. The performance of the proposed approach is validated by numerical simulations.

Direct Adaptive Fuzzy Sliding Mode Control for Under-actuated Uncertain Systems

  • Su, Shun-Feng;Hsueh, Yao-Chu;Tseng, Cio-Ping;Chen, Song-Shyong;Lin, Yu-San
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.4
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    • pp.240-250
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    • 2015
  • The development of the control algorithms for under-actuated systems is important. Decoupled sliding mode control has been successfully employed to control under-actuated systems in a decoupling manner with the use of sliding mode control. However, in such a control scheme, the system functions must be known. If there are uncertainties in those functions, the control performance may not be satisfactory.In this paper, the direct adaptive fuzzy sliding mode control is employed to control a class of under-actuated uncertain systems which can be regarded as a combination of several subsystems with one same control input. By using the hierarchical sliding control approach, a sliding control law is derived so as to make every subsystem stabilized at the same time. But, since the system considered is assumed to be uncertain, the sliding control law cannot be readily facilitated. Therefore, in the study, based on Lyapunov stable theory a fuzzy compensator is proposed to approximate the uncertain part of the sliding control law. From those simulations, it can be concluded that the proposed compensator can indeed cope with system uncertainties. Besides, it can be found that the proposed compensator also provide good robustness properties.

Air Pollution Reduction Strategies of World Major Ports

  • Han, Chul-Hwan
    • THE INTERNATIONAL COMMERCE & LAW REVIEW
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    • v.48
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    • pp.27-56
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    • 2010
  • Pollution emissions from international shipping and port activities have a significant impact on public health and global climate changes. The purpose of this paper is to review the status of pollution mitigation measures implemented to date in port industry and find out some implications for Korean ports. For this aim, the clean air strategies of the world major ports including six USA ports (Los Angeles/Long Beach, Now York/New Jersey, and Seattle and Tacoma), two European ports (Rotterdam and Gothenburg) and Busan Port were considered. Various measures to reduce emission from ports are evaluated by sectors-ocean going vessels, cargo handling equipments, truck and rail-, on the basis of categories such as reduction control technologies, operational changes and market-based measures. The policy implications of this paper are as follows. First, Clean Air Act Plans of Korean ports are required as soon as possible. Second, integrated approach is required to reduce emission effectively. Finally, the effect of port-related emission reduction can be maximized when various measures are conducted on a regional basis including neighboring ports. Furthermore, regional or global-based approach is useful to guarantee the level playing field among ports.

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A Robust Control with The Bound Function of Neural Network Structure for Robot Manipulator

  • Chul, Ha-In;Chul, Han-Myung
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.113.1-113
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    • 2001
  • The robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The neural network structure presents the bound function and does not need the concave property of the bound function, The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulators.

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Robust $L_2$Optimization for Uncertain Systems

  • Kim, Kyung-Soo;Park, Youngjin
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.348-351
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    • 1995
  • This note proposes a robust LQR method for systems with structured real parameter uncertainty based on Riccati equation approach. Emphasis is on the reduction of design conservatism in the sense of quadratic performance by utilizing the uncertainty structure. The class of uncertainty treated includes all the form of additive real parameter uncertainty, which has the multiple rank structure. To handle the structure of uncertainty, the scaling matrix with block diagonal structure is introduced. By changing the scaling matrix, all the possible set of uncertainty structures can be represented. Modified algebraic Riccati equation (MARE) is newly proposed to obtain a robust feedback control law, which makes the quadratic cost finite for an arbitrary scaling matrix. The remaining design freedom, that is, the scaling matrix is used for minimizing the upper bound of the quadratic cost for all possible set of uncertainties within the given bounds. A design example is shown to demonstrate the simplicity and the effectiveness of proposed method.

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Dynamic Control Allocation for Shaping Spacecraft Attitude Control Command

  • Choi, Yoon-Hyuk;Bang, Hyo-Choong
    • International Journal of Aeronautical and Space Sciences
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    • v.8 no.1
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    • pp.10-20
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    • 2007
  • For spacecraft attitude control, reaction wheel (RW) steering laws with more than three wheels for three-axis attitude control can be derived by using a control allocation (CA) approach.1-2 The CA technique deals with a problem of distributing a given control demand to available sets of actuators.3-4 There are many references for CA with applications to aerospace systems. For spacecraft, the control torque command for three body-fixed reference frames can be constructed by a combination of multiple wheels, usually four-wheel pyramid sets. Multi-wheel configurations can be exploited to satisfy a body-axis control torque requirement while satisfying objectives such as minimum control energy.1-2 In general, the reaction wheel steering laws determine required torque command for each wheel in the form of matrix pseudo-inverse. In general, the attitude control command is generated in the form of a feedback control. The spacecraft body angular rate measured by gyros is used to estimate angular displacement also.⁵ Combination of the body angular rate and attitude parameters such as quaternion and MRPs(Modified Rodrigues Parameters) is typically used in synthesizing the control command which should be produced by RWs.¹ The attitude sensor signals are usually corrupted by noise; gyros tend to contain errors such as drift and random noise. The attitude determination system can estimate such errors, and provide best true signals for feedback control.⁶ Even if the attitude determination system, for instance, sophisticated algorithm such as the EKF(Extended Kalman Filter) algorithm⁶, can eliminate the errors efficiently, it is quite probable that the control command still contains noise sources. The noise and/or other high frequency components in the control command would cause the wheel speed to change in an undesirable manner. The closed-loop system, governed by the feedback control law, is also directly affected by the noise due to imperfect sensor characteristics. The noise components in the sensor signal should be mitigated so that the control command is isolated from the noise effect. This can be done by adding a filter to the sensor output or preventing rapid change in the control command. Dynamic control allocation(DCA), recently studied by Härkegård, is to distribute the control command in the sense of dynamics⁴: the allocation is made over a certain time interval, not a fixed time instant. The dynamic behavior of the control command is taken into account in the course of distributing the control command. Not only the control command requirement, but also variation of the control command over a sampling interval is included in the performance criterion to be optimized. The result is a control command in the form of a finite difference equation over the given time interval.⁴ It results in a filter dynamics by taking the previous control command into account for the synthesis of current control command. Stability of the proposed dynamic control allocation (CA) approach was proved to ensure the control command is bounded at the steady-state. In this study, we extended the results presented in Ref. 4 by adding a two-step dynamic CA term in deriving the control allocation law. Also, the strict equality constraint, between the virtual and actual control inputs, is relaxed in order to construct control command with a smooth profile. The proposed DCA technique is applied to a spacecraft attitude control problem. The sensor noise and/or irregular signals, which are existent in most of spacecraft attitude sensors, can be handled effectively by the proposed approach.

Adaptive Fuzzy Neural Control of Unknown Nonlinear Systems Based on Rapid Learning Algorithm

  • Kim, Hye-Ryeong;Kim, Jae-Hun;Kim, Euntai;Park, Mignon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09b
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    • pp.95-98
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    • 2003
  • In this paper, an adaptive fuzzy neural control of unknown nonlinear systems based on the rapid learning algorithm is proposed for optimal parameterization. We combine the advantages of fuzzy control and neural network techniques to develop an adaptive fuzzy control system for updating nonlinear parameters of controller. The Fuzzy Neural Network(FNN), which is constructed by an equivalent four-layer connectionist network, is able to learn to control a process by updating the membership functions. The free parameters of the AFN controller are adjusted on-line according to the control law and adaptive law for the purpose of controlling the plant track a given trajectory and it's initial values are off-line preprocessing, In order to improve the convergence of the learning process, we propose a rapid learning algorithm which combines the error back-propagation algorithm with Aitken's $\delta$$\^$2/ algorithm. The heart of this approach ls to reduce the computational burden during the FNN learning process and to improve convergence speed. The simulation results for nonlinear plant demonstrate the control effectiveness of the proposed system for optimal parameterization.

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Path Tracking Controller Design for Surface Vessel Based on Sliding Mode Control Method with Switching Law (슬라이딩 모드 제어와 스위칭 기법에 기반한 수상함의 경로 추종 제어기 설계)

  • Lee, JunKu
    • Journal of the Korea Institute of Military Science and Technology
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    • v.20 no.1
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    • pp.108-118
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    • 2017
  • In this paper, the path tracking controller for a surface vessel based on the sliding mode control (SMC) with the switching law is proposed. In order to have no restriction on movement and improved tracking performance, the proposed control system is developed as follows: First, the kinematic and dynamic models in Cartesian coordinates are considered to solve the singularity problem at the origin. Second, the new multiple sliding surfaces are designed with the SMC and approach angle concept to solve the under-actuated property. Third, the switching control system is designed to improve tracking performance. To prove the stability of the proposed switching system under the arbitrary switching, the Lyapunov stability analysis method with the common Lyapunov function is used. Finally, the computer simulations are performed to demonstrate the performance, effectiveness and stability of the proposed tracking controller of a surface vessel.