• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.3
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• pp.250-254
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• 2008

Robot actuators are significantly important with respect to whole control system performance. This paper presents an adaptive control approach for flexible robot actuators with time-varying spring and damping nature. We first represent a perturbed system model with assumption that its information are partially known. Nominal model reference control method is employed for deriving our adaptive control law. We carry out numerical simulation to evaluate the proposed control system and compare simulation results to a well-known control method for demonstrating its effectiveness.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.109-117
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• 1999

In this paper, a direct adaptive control, based on Lyapunov Function Candidate, is applied to a nonlinear Gunner's Primary Stabilized Head Mirror system to derive a parameter adaptation scheme; furthemore, a nonlinear sliding mode control, but also compensating the error in identification of the parameters which are even varying of have uncertain values. The performance of the adaptive controller is determined by the tracking ability to a desired model under some disturbances and the slowly varying parameters of the system. Both adaptive scheme and sliding mode play an important fole in the improvement of the nonlinear system control.

• KIEE International Transaction on Systems and Control
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• v.2D no.2
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• pp.108-114
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• 2002

This paper describes the design of a robust adaptive controller for a nonlinear dynamical system with unknown nonlinearities. These unknown nonlinearities are approximated by multilayered neural networks (MNNs) whose parameters are adjusted on-line, according to some adaptive laws far controlling the output of the nonlinear system, to track a given trajectory. The main contribution of this paper is a method for considering input constraint with a rigorous stability proof. The Lyapunov synthesis approach is used to develop a state-feedback adaptive control algorithm based on the adaptive MNN model. An overall control system guarantees that the tracking error converges at about zero and that all signals involved are uniformly bounded even in the presence of input saturation. Theoretical results are illustrated through a simulation example.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1821-1826
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• 2009

An adaptive neural controller for perturbed strict-feedback nonlinear system is proposed. All the previous adaptive neural (or fuzzy) controllers are based on the backstepping scheme where the universal approximators are employed in every design steps. These schemes involve virtual controls and their time derivatives that make the stability analysis and implementation of the controller very complex. This fact is called 'explosion of complexty ' since the complexity grows exponentially as the system dynamic order increases. The proposed adaptive neural control scheme adopt the backstepping design procedure only for determining ideal control law and employ only one neural network to approximate the finally selected ideal controller, which makes the controller design procedure and stability analysis considerably simple compared to the previously proposed controllers. It is shown that all the time-varing signals containing tracking error are stable in the Lyapunov viewpoint.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.92-99
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• 2016

An electro-hydraulic actuator (EHA) is widely used in industrial motion systems and the increasing bandwidth of EHA position control is important issue. The model-inverse feedforward controller is known to extend the bandwidth of system. When the system has non-minimum phase (NMP) zeros, direct model inversion makes system unstable. To overcome this problem, an approximate model-inverse method is used. A representative approximate model inversion method is zero phase error tracking control (ZPETC). However, if zeros locate right half plane of z-plane, the approximate inverse model amplifies the high-frequency response. In this paper, to solve the problem of ZPETC, an adaptive model-inverse control is proposed. The adaptive algorithm updates feedforward term in real-time. The effectiveness of the proposed adaptive model-inverse position control strategy is verified by comparison with typical proportional-integral (PI) control and feedforward control by experiments. As a result, the proposed adaptive controller extends the bandwidth of EHA position control.

• Smart Structures and Systems
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• v.10 no.1
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• pp.33-46
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• 2012

To reduce the vibration of cable-stayed bridges, conventional magnetorheological (MR) damper control system (CMRDS), with separate power supply, sensors and controllers, is widely investigated. In this paper, to improve the reliability and performance of the control system, one adaptive MR damper control system (AMRDS) consisting of MR damper and piezoelectric energy harvester (PEH) is proposed. According to piezoelectric effect, PEH can produce energy for powering MR damper. The energy is proportional to the product of the cable displacement and velocity. Due to the damping force changing with the energy, the new system can be adjustable to reduce the cable vibration. Compared with CMRDS, the new system is structurally simplified, replacing external sensor, power supply and controller with PEH. In the paper, taking the N26 cable of Shandong Binzhou Yellow River Bridge as example, the design method for the whole AMRDS is given, and simple formulas for PEH are derived. To verify the effectiveness of the proposed adaptive control system, the performance is compared with active control case and simple Bang-Bang semi-active control case. It is shown that AMRDS is better than simple Bang-Bang semi-active control case, and still needed to be improved in comparison with active control case.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1221-1224
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• 1996

As in most industrial processes, the dynamic characteristics of an electric power system are subject to changes. Amongst those effects which cause the system to be uncertain, faults on transmission lines are considered. For the stabilization of the power system, we present an indirect adaptive control method, which is capable of tracking a sudden change in the effective reactance of a transmission line. As the plant dynamics are nonlinear, an input-output feedback linearization method is combined with an identification algorithm which estimates the effect of a fault.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.486-493
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• 2000

This paper presents an application to a multimachine power system of power system stabilizer using revised pole shift adaptive algorithm. Controller parameters are determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameters of controller and overcome the problem of pole placement algorithm, this paper presents pole shift algorithm revised pole shift factor. Also, the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping characteristics. The results tested on a multimachine power system verify that the proposed controller has better dynamic and transient performance than conventional controller.

• Journal of Mechanical Science and Technology
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• v.16 no.12
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• pp.1613-1626
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• 2002

This paper presents hybrid control of an active suspension system with a full-car model by using H$\sub$$\infty$/ and nonlinear adaptive control methods. The full-car model has seven degrees of freedom including heaving, pitching and rolling motions. In the active suspension system, the controller shows good performance: small gains from the road disturbances to the heaving, pitching and rolling accelerations of the car body. Also the controlled system must be robust to system parameter variations. As the control method, H$\sub$$\infty$/ controller is designed so as to guarantee the robustness of a closed-loop system in the presence of uncertainties and disturbances. The system parameter variations are taken into account by multiplicative uncertainty model and the system robustness is guaranteed by small gain theorem. The active system with H$\sub$$\infty$/ controller can reduce the accelerations of the car body in the heaving, pitching and rolling directions. The nonlinearity of a hydraulic actuator is handled by nonlinear adaptive control based on the back-stepping method. The effectiveness of the controllers is verified through simulation results in both frequency and time domains.