Papers by Keyword: Nonlinear Control

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Authors: Kenji Nakajima, Hiroyuki Saitou, Seiji Hashimoto
Abstract: In this paper, a high precision positioning control method based on the learning algorithm with the reference model is proposed. The reference model is composed of a plant model and a feedback controller. In the proposed control method, disturbance, modeling error and nonlinear characteristic can be effectively compensated by the neural network-based controller, which learns the reference model. Moreover, the control-input saturation problem due to the over-learning for the neural network can be avoided. The effectiveness of the proposed control method is experimentally verified using the precision positioning equipment with nonlinear friction characteristics.
Authors: Lu Juan Shen, Ye Bao, Jian Ping Cai
Abstract: In this paper, a class of gun control system of tank is considered with uncertain parameters and the backlash-like hysteresis which modeled by a differential equation. An adaptive control law is designed with backstepping technique. Compared to exist results on tank gun control problem , in our control scheme, the effect of backlash hysteresis is considered completely than to be linearized simply and no knowledge is assumed on the uncertain parameters. the stability of closed loop system and the tracking performance can be guaranteed by this control law. Simulation studies show that this controller is effective.
Authors: Huan Yu Luo, Hong Ze Xu
Abstract: This paper investigates the tracking control problem of high-speed train system. The nonlinearities and uncertainties exist during the train operation are becoming even worse and cannot be ignored or simply linearized anymore as the speed increases. An adaptive control algorithm is developed to improve the tracking performance that does not rely on the accurate model parameters which are impossible to obtain precisely in practice and can deal with the nonlinearities efficiently. Based on the Lyapunov stability theory, the backstepping design method is used to deduce the control law step by step, and the certainty-equivalent principle is employed to dispose the uncertain parameters. Both the rigorous theoretical analysis and simulation results are all verified the effectiveness of this proposed control algorithm.
Authors: Amezquita S. Kendrick, Lin Yan, Waseem Aslam Butt
Abstract: An adaptive dynamic surface control scheme for actuator failures compensation in a class of nonlinear system is presented. Radial basis function neural networks (RBF NNs) are incorporated into our controller design, for approximating the nonlinearities around the known nominal model. The RBF NNs compensate the system dynamics uncertainties and disturbance induced by actuator failures. The closed-loop signals of the system are proven to be uniformly ultimately bounded (UUB) by Lyapunov analysis. The output tracking error is bounded within a residual set which can be made small by appropriately choosing the controller parameters. We show the effectiveness of our approach by simulating the longitudinal dynamics of a twin otter aircraft with half portion of the elevator failing at unknown value and time instant.
Authors: Suwat Kuntanapreeda
Abstract: Shape memory alloy (SMA) actuators are promising for miniature applications. They accomplish the shape memorization via a temperature dependent phase transformation process. Control of SMA actuators is challenging because the actuators exhibit highly hysteresis behavior. This paper presents a fuzzy-based position control scheme for a SMA actuated mass system. The control system consists of an outer-and an inner-control loop. The inner loop controls the temperature of the SMA actuators using a PI controller, whereas the outer loop, which is affected by the hysteresis of the SMA actuators, controls the position. To deal with the hysteresis in the position control loop, an adaptive fuzzy sliding-mode control method is adopted. Experimental results illustrate the success of the proposed control scheme.
Authors: Li Xin Li, Zhong Qing Jin
Abstract: This study mainly addresses the adaptive control for the levitation system in presence of mass variation. Firstly, considering the nonlinear of levitation system, the feedback linearization is applied to achieve the global stabilization. Due to the additions of luggage and passengers, the variation of mass degrades the dynamic performance of levitation system, it is necessary to estimate and cancel the effect of mass variation. So an algorithm to estimate the mass of levitation system is proposed and integrated to adjust the parameters on line. The results of simulations show that excellent closed-loop performance is provided in the presence of mass variation.
Authors: Hong Ge Zhao
Abstract: This paper proposes a robust adaptive neural network controller (RANNC) for electrode regulator system. An equivalent model in affine-like is derived for electrode regulator system. Then, the nonlinear control law is derived directly based on the affine-like equivalent model identified with neural networks, which avoids complex control development and intensive computation. Pretraining is not required and the weights of the neural networks used in adaptive control are directly updated online based on the input-output measurement. The proposed nonlinear controller is verified by computer simulations.
Authors: Zhan Qi Fan, Lin Liu, Xun Sun
Abstract: An improved large envelope nonlinear flight control method using active disturbances rejection control (ADRC) method and wavelet neural network is approved in this paper. Wavelet neural network is used to realize the inversion of the 6-DOF nonlinear airplane model. The wavelet neural network is optimized using simulated annealing particle swarm optimization algorithm to improve the approach precision. In order to improve the robustness and control performance in all disturbances, ADRC is used to realize the high precision flight control. The simulation results show that the large envelope flight controller has excellent control performance.
Authors: Zeng Ji Chen, Wei Min Fang, Cong Rong Guan
Abstract: In order to reduce excitation system swing and resultant reactive power swing, namely, reduce external electromagnetic interference to stable operation of 600MW generating unit, the paper analyses unit excitation control mode and designs hardware and software of excitation system. First, digital microcomputer control system organization was designed based on nonlinear control theory, which had an increase of control mode such as PID control mode, nonlinear optimum electronic control (NOEC) mode besides original voltage difference and current control mode. Second, full duplex collocation configuration mode of excitation system was designed, namely two controllers were master-slave concurrent, and each controller could meet excitation requirement of various operation condition including constrained excitation. Finally, in electric network disturbance test, measured excitation system parameters recovered stably in 1020 ms such as stator voltage Ut, rotor voltage Uf, comprehensive amplified control voltage Uc, active power P and reactive power Q. It is verified that transient stability and unit operating condition are improved.
Authors: Wei Zhou, Bao Bin Liu
Abstract: In view of parameter uncertainty in the magnetic levitation system, the adaptive controller design problem is investigated for the system. Nonlinear adaptive controller based on backstepping is proposed for the design of the actual system with parameter uncertainty. The controller can estimate the uncertainty parameter online so as to improve control accuracy. Theoretical analysis shows that the closed-loop system is stable regardless of parameter uncertainty. Simulation results demonstrate the effectiveness of the presented method.
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