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This paper describes a neural network controller for autonomous underwater vehicles (AUVs). The designed online multilayer perceptron neural network (OMLPNN) calculates forces and moments in earth fixed frame to eliminate the tracking errors of AUVs whose dynamics are highly nonlinear and time varying. Another OMLPNN has been designed to generate an inverse model of AUV, which determine the appropriate...
In this paper the elevation and traveling control strategy -fuzzy logic which is based on the LQR for a helicopter with three degrees of freedom is considered. The characteristic of channel coupling and nonlinearity of the system will be resolved by dividing the workplace into 4 phases which the system has a linear behavior, the phases are independently considered and LQR controllers are designed...
Robust and adaptive controller of the uncertain mobile manipulator with holonomic and non-holonomic constrains is designed. Considering some problems in model reduction by implicit function theorem when the mobile manipulator subjects to holonomic and non-holonomic constrains, an uniform expression of holonomic and non-holonomic constrains is introduced, and then based on the reduced model, a steady...
This paper presents the method of discrete-time sliding mode control (DT-SMC) for a class of nonlinear time-delay systems via Takagi-Sugeno (T-S) fuzzy model. First, the discrete-time linear model with uncertainties and tine-varying delay is derived by employing T-S model to represent original system. Then the control problem becomes the robust stabilization controller design for linear uncertain...
A global sliding mode variable structure controller based on fuzzy logic is adopted to Permanent magnet Synchronous Motor. First,. the controller can ensure sliding behavior throughout an entire response, we can specify the demands on the capability of the system to achieve a desired performance. Moreover, the control law is based on equivalent control, in which the function sign(·)is substituted...
This paper investigates the problem of static output feedback H∞ control for a class of nonlinear systems via a linear matrix inequality (LMI) approach. The considered system is approximated by the Takagi-Sugeno (T-S) fuzzy model. Based on a Lyapunov functional method, we develop a H∞ control law which makes the closed-loop system is asymptotically stable with guaranteed H∞ performance. In contrast...
The dynamics of a multi machine power system are both nonlinear and interconnected. The equilibrium of such a system is typically unknown and uncertain, and the controllers within are also subject to physical limitations. Based on the latest development of nonlinear H∞ robust control theory, a control design is applied to stabilize the linearized uncertain system using Glover-McFarlane's loop shaping...
This paper studies the primary control problem of a vibrating MEMS gyroscope. A nonlinear robust adaptive control scheme is proposed for the drive axis of a vibrating MEMS gyroscope with parametric uncertainties and exogenous disturbances. By combining the dynamic surface control (DSC) method with H∞ disturbance attenuation technique, a simpler systematic design procedure is developed. The derived...
The tracking control problem of Duffing-Holmes chaotic systems containing unknown parameters is studied. Based on the backstepping design method, special barrier functions are employed in Lyapunov synthesis. The derived adaptive robust controller guarantees the closed-loop system globally uniformly ultimate bound, and the tracking error is convergent to a small neighborhood of zero. In addition, the...
Aiming at the characteristics such as multivariable, strong coupling, nonlinear and time-varying parameters for the coordinated control system of unit power plant, a single-nerve cell network combined with PID control method was presented. A modified mutative scale chaotic optimization algorithm was proposed for the use of tuning the weight parameters of neural network and PID parameters. The new...
It is difficult to express accurately nonlinear characteristics of the bulb turbogenerators with mathematical model. The artificial neural network has more characteristics, such as self-learning, adaptive, distributed parallel, fault-tolerance, memory functions and so on. This paper presents the characteristics of neural network to model for bulb turbogenerators. The results obtained from the nonlinear...
An adaptive output feedback controller based on neural network(NN) is proposed, which forces a waterjet propulsion ship to track a desired course. A nonlinear course model of waterjet propulsion ship is proposed. The proposed control method only need the measurable information of course angle, and the unknown disturbances in the complicated sea states are estimated by neural network, so the control...
A robust sliding mode observer is presented in this paper. The design of the observer's parameters needs not to solve a lot of equations. The observer proposed in the paper is robust to the nonlinearities and/or uncertainties of systems. The convergence rate between the observer and the system can be changed by choosing suitable sliding mode manifold, so that to attain the desired performances. Simulation...
In this paper, a novel fuzzy modeling method is developed for a class of nonlinear system. The idea comes from the concepts of the Takagi-Sugeno (T-S) fuzzy modeling technique, and this method is especially suitable for the nonaffine nonlinear system. Firstly, an inverted pendulum mounted on motor-driven cart is illustrated to demonstrate the validity of modeling result. Besides this example, a nonaffine...
This paper focuses on the problem of guaranteed cost control of uncertain time-varying delay systems. Stability and stabilization conditions are first proposed, and sufficient conditions for the existence of guaranteed cost controllers are given in terms of linear matrix inequalities (LMI). Furthermore, a convex optimization problem with LMI constraints is formulated to design the optimal guaranteed...
This paper introduces a new methodology to synthesize automatically robust controllers in the Quantitative Feedback Theory (QFT) framework. The method avoids the classical gridding of the controller's phase, and deals with multi-objective specifications and parametric uncertainty in the plant model. By tacking the required robust stability and robust performance specifications, and grouping them into...
This paper presents a robust adaptive controller for time-varying systems with unknown dead-zone nonlinearity at the plant input. The controller is designed based on the pole assignment strategy, and it is applicable even to systems in the presence of unmodeled dynamics, bounded external disturbances and time-varying parameters. The global stability is ensured by the proposed controller.
This paper considers semi-global robust finite time stabilization of non-holonomic chained form systems with perturbed terms. The objective is to design a non-smooth state feedback law such that the controlled chained form system is both Lyapunov stable and finite-time convergent within any given settling time for any given initial states. We propose a novel switching control strategy with help of...
Internet congestion control system is complex, uncertainty and nonlinear. An Improved PID Neural Network (I-PID-NN) controller with changing integration rate and incomplete derivation in hidden layer is applied in active queue management (AQM). The adjustment of neural network parameters are implemented by using gradient algorithm as learning the rules, and the probability of packet loss can achieve...
The paper proposes a new fuzzy identification method based on H∞ error estimation for the issues of robust identification of fuzzy model. The H∞ state estimation is applied to the parameter identification of fuzzy model in the paper. The presented algorithm not only guarantees to satisfy a specified level of robustness, and also provides an optimized error upper bound. Finally, we study the fuzzy...
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