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This paper is concerned with robust stochastic stabilization problem for a class of uncertain stochastic fuzzy systems. The purpose is to design a state-feedback fuzzy controller such that the resulting closed-loop system is robustly stochastically asymptotically stable. Sufficient conditions for the solvability of this problem are obtained by using matrix operations and stochastic Lyapunov approach...
Adaptive nonlinear output feedback control of GD-FNN(generalized dynamic fuzzy neural network) for underwater robot motion control using forming filter for wave disturbance is presented. This method completely construct nonlinear and uncertain parts of underwater robot by online adaptive learning algorithm without knowing fuzzy neural structure and training phase in advance. Output feedback control...
This paper presents a new adaptive controller for visual servoing of robot manipulators based on the concept of depth-independent interaction matrix. By mapping the image error onto the joint space using the depth-independent interaction matrix, it is possible to make the unknown 3-D coordinates of the feature points linearly appear in the closed-loop dynamics of the system, so the unknown coordinates...
This paper is concerned with the quantized stabilization of linear discrete systems with packet dropout. Based on the zoom strategy and Lyapunov theory, for a given packet dropout rate, a sufficient condition is given for closed-loop system to be mean square stable. A numerical simulation is presented to show the effectiveness of the main result.
This paper mainly deals with the problem of designing reduced order observer-based strictly dissipative controllers for linear singular systems. By using Lyapunov function and linear matrix inequalities(LMI) method, sufficient conditions are obtained for the existences of the observers and the controllers, and the corresponding design methods are also given in terms of the solutions of linear matrix...
In this paper, a novel adaptive neural network (NN) dynamic surface control(DSC) is developed for a class of strict-feedback nonlinear systems with unknown virtual control gain functions. The explosion of complexity in traditional backstepping design is avoided by utilizing dynamic surface control and introducing integral-type Lyapunov function. Using Young's inequality, only one parameter is adjusted...
Utilizing the notion of Filippov solution, a sliding mode control law is derived for generic second order nonlinear mechanical system with friction. The control law is designed with some tunable parameters and optional functions. The asymptotically stability of the closed-loop system is proved by the concept of the solution, nonsmooth analysis and nonsmooth Lyapunov stability theory. By some numerical...
In order to analyze the performance of control system affected by scheduling in networked control system (NCS), the guaranteed cost control (GCC) is researched integrating network scheduling. A scheduling model of NCS is established with communication constraint on input and feedback channels. Utilizing communication sequence to express the instance of scheduling, the model can be transform into uncertain...
Based on observer, delay-dependent robust H∞ controller design problem for time-delay systems with a class of nonlinear uncertainties is discussed in the paper. Assuming that the nonlinear uncertain functions in the considered model are gain-bounded, we obtain a sufficient condition for the robustly asymptotic stability and H∞ performance of the closed-loop system in the light of Lyapunov stability...
There are five stochastic search algorithms had been designed to optimize the adaptive parameter in predictive functional controller based on Kautz model. They are exhaustive method, local search, particle swarm optimization, chaotic search and genetic optimization. The state stability condition for closed-loop system was given based on Lyapunov stability theory. Their validity had been verified by...
Aiming at a class of strict-feedback nonlinear systems with mismatched uncertainties, an adaptive backstepping fuzzy controller design is presented. By applying backstepping design strategy and online approaching uncertainties with fuzzy approximator, the control inputs and adaptive tuning rules are derived from the Lyapunov stability theory. To deal with the problem of extreme expanded operation...
For the DC chassis dynamometer, a nonlinear mathematical model was established based on the analysis of the transmission system of the DC dynamometer, and an adaptive controller based on RBF NN (radial basis function neural network) was proposed to control a dynamometer to load resistance intelligently to achieve stepless simulation of inertia. By using the Lyapunov synthesis approach, it was proved...
In this paper, adaptive tracking control is investigated for a class of nonlinear time-delay systems with actuator saturation nonlinearity. The uncertain time-delay function is bounded by a nonlinear function with unknown coefficients. The actuator saturation nonlinearity is assumed to be nonsymmetric and unknown. Neural network approximation techniques are utilized to compensate the saturation nonlinearity...
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