• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.32 no.3
• /
• pp.280-289
• /
• 2008

This paper presents design of the quantitative feedback control system of the three axes hydraulic road simulator with respect to the dummy wheel for uncertain multiple input-output(MIMO) feedback systems. This simulator has the uncertain parameters such as fluid compressibility, fluid leakage, electrical servo components and nonlinear mechanical connections. This works have reproduced the random input signal to implement the real road vibration's data in the lab. The replaced $m^2$ MISO equivalent control systems satisfied the design specifications of the original $m^*m$ MIMO control system and developed the mathematical method using quantitative feedback theory based on schauder's fixed point theorem. This control system illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) having the minimum bandwidth for parameters of uncertain plant. The efficacy of the designed controller is verified through the dynamic simulation with combined hydraulic model and Adams simulator model. The Matlab simulation results to connect with Adams simulator model show that the proposed control technique works well under uncertain hydraulic plant system. The designed control system has satisfied robust performance with stability bounds, tracking bounds and disturbance. The Hydraulic road simulator consists of the specimen, hydraulic pump, servo valve, hydraulic actuator and its control equipments

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.1
• /
• pp.103-113
• /
• 2018

In this paper, an improved integral variable structure regulation controller is designed by using a special integral sliding surface and a disturbance observer for the improved regulation control of highly nonlinear rigid robot manipulators with prescribed output performance. The sliding surface having the integral state with a special initial condition is employed in this paper to exactly predetermine the ideal sliding trajectory from a given initial condition to the desired reference without any reaching phase. And a continuous sliding mode input using the disturbance observer is also introduced in order to effectively follow the predetermined sliding trajectory within the prescribed accuracy without large computation burden. The performance of the prescribed tracking accuracy to the predetermined sliding trajectory is clearly investigated in detail through the two theorems, together with the closed loop stability. The design of the proposed regulation controller is separated into the performance design and robustness design in each independent link. The usefulness of the algorithm has been demonstrated through simulation studies on the regulation control of a two-link robot under parameter uncertainties and payload variations.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.32 no.4
• /
• pp.24-33
• /
• 2004

In this paper, the helicopter flight control system using online adaptive neural networks which have the universal function approximation property is considered. It is not compensation for modeling errors but approximation two functions required for feedback linearization control action from input/output of the system. To guarantee the tracking performance and the stability of the closed loop system replaced two nonlinear functions by two neural networks, weight update laws are provided by Lyapunov function and the simulation results in low speed flight mode verified the performance of the control system with the neural networks.

• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.731-736
• /
• 1994

Experiment on a lab-scale pH process is carried out to evaluate the control performance of the neural linearizing control scheme(NLCS) using a radial basis function(RBF) network which was previously proposed by Kim and Park. NLCS was developed to overcome the difficulties of the conventional neural controllers which occur when they are applied to chemical processes. Since NLCS is applicable for the processes which are already controlled by a linear controller and of which the past operating data are enough, we first control the pH process with PI controller. Using the operating data with PI controller, the linear reference model is determined by optimization. Then, a IMC controller replaces the PI controller as a feedback controller. NLCS consists of the IMC controller and a RBF network. After the learning of the neural network is fully achieved, the dynamics of the process combined with the neural network becomes linear and close to that of the linear reference model and the control performance of the linear control improves. During the training, NLCS maintains the stability and the control performance of the closed loop system. Experimental results show that the NLCS performs better than PI controller and IMC for both the servo and the regulator problems.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.5
• /
• pp.452-461
• /
• 2007

Adaptive anti-sway and trajectory tracking control of overhead crane is presented, which utilizes Fuzzy Uncertainty Observer(FUO) and Fuzzy based Variable Structure Control(FVSC). We consider an overhead crane system which can be decoupled into the actuated and unactuated subsystems with its own lumped uncertainty such as parameter uncertainties and external disturbance. First, a new method for anti-sway control using FVSC is proposed to improve the conventional method based on Lyapunov direct method, while a conventional trajectory tracking control law using feedback linearization is directly adopted. Second, FUO is designed to estimate one of the two lumped uncertainties which can compensate both of them, based on the fact that two lumped uncertainties are coupled with each other. Then, an adaptive anti-sway control is proposed by incorporating the proposed FVSC and FUO. Under the condition that the observation error is Uniformly Ultimately Bounded(UUB) within an arbitrarily shrinkable region, the overall closed-loop system is shown to be Globally Uniformly Ultimately Bounded(GUUB). In addition, the Global Asymptotic Stability(GAS) of it is shown under the vanishing disturbance assumption. Finally, the effectiveness of the proposed scheme has been confirmed by numerical simulations.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.11
• /
• pp.1040-1044
• /
• 2012

We design a NCS (Networked Control System) where the communication between sensors and controllers takes place over a USN (Ubiquitous Sensor Network). In order to measure time delays between sensors and controllers in real time, we design an algorithm to measure RTT (Round Trip Time) between USN nodes, and implement it into TinyOS of USN. By using the measured time delays, we construct the Smith predictor to compensate the time delays between sensors and controllers in real-time. For the real time experiment, we simulate the dynamic plant model, controller, and USN interface using Real-Time Windows Target provided in MATLAB. The USN interface in the Simulink model consists of serial ports, which connect the plant output and controller with USN nodes. The experiment results show that the time delays between sensors and controllers are precisely measured in real time; the Smith predictor appropriately compensates the time delays; and the stability is achieved in the closed-loop of the NCS.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.37 no.6
• /
• pp.15-24
• /
• 2000

This paper presents an output feedback robust H$\infty$ control problem for a class of uncertain nonlinear systems, which can be represented by an fuzzy dynamic model. The nonlinear system is represented by Takagi-Sugeno fuzzy model, and the control design is carried out on the basis of the fuzzy model. Using a single quadratic Lyapunov function, the globally exponential stability and disturance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust H$\infty$ controllers are given in terms of linear matrix inequalities(LMIs). Constructive algorithm for design of robust H$\infty$ controller is also developed. The resulting controller is nonlinear and automatically tuned based on fuzzy operation.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.10 no.3
• /
• pp.357-364
• /
• 2015

This research presents a DC-DC converter controller implemented with an analog memory. The structure of the converter will contribute to solve the stability problem unavoidable in a conventional closed loop converter. The analog memory will be used for realizing CAM(Contents Addressable Memory) which contains the output of the converter and the relevant duty ratio, respectively. The operation for reading in the memory is executed with an absolute differencing circuit and a WTA(Winner-Take-All) circuit suitable for a nearest-match function of the CAM. We also present a system architecture that enables highly-paralleled fast writing and quick readout as well as high integration density.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.7
• /
• pp.621-627
• /
• 2001

In this paper, a novel and efficient global intelligent digital redesign technique for a Takagi-Sugeno (TS) fuzzy system is addressed. The proposed method should be notably discriminated from the previous works in that in allows us to globally match the states of the closed-loop TS fuzzy system with the pre-designed continuous-time fuzzy-model-based controller and those with the digitally redesigned fuzzy-model-based controller, and further to guarantee the stabilizability by the redesigned controller in the sense of Lyapunov. Sufficient conditions for the global state-matching and the stability of the digitally controller system are formulated in terns of linear matrix inequalities (LMIs). The Duffing-like chaotic oscillator is simulated and demonstrated, to validate the effectiveness of the proposed digital redesign technique, which implies the safe applicability to the digital control system.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.1
• /
• pp.46-50
• /
• 2013

This paper proposes an adaptive fault accommodation control approach for flexible-joint (FJ) robots with multiple actuator faults. It is assumed that the value and occurrence time of multiple actuator faults are unknown. An adaptive fault accommodation control scheme with prescribed performance bounds, which characterize the convergence rate and maximum overshoot of tracking errors, is designed to accommodate the actuator faults. From the Lyapunov stability theorem, it is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded and tracking errors are preserved within prescribed performance bounds regardless of actuator faults.