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In this paper the problems of H∞ performance analysis and control of networked control systems with time varying sampling intervals and delays are studied. A new impulsive system based method is introduced to deal with this problem. Moreover, a new Lyapunov-Krasovskii functional is proposed to establish sufficient conditions for exponential stability and H∞ control of networked control systems. The...
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...
In this paper, adaptive NN (neural network) tracking control is proposed for ocean surface vessels with parametric uncertainties, unknown disturbances and rotary actuators. Based on the Lyapunov synthesis method and backstepping technique, adaptive NN tracking control is developed by incorporating the actuator configuration matrix and considering actuator saturation constraints. In the proposed adaptive...
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...
The Leader/Follower formation control of mobile robots with uncertain dynamical models is investigated in this paper and adaptive shape tracking controller is developed for the follower. Firstly, a kinematic shape tracking controller is presented based on the formation equation, then the shape tracking error equation is derived with backstepping technology and a direct adaptive dynamical shape tracking...
The high precision of a piezo-electric positioning stage almost depends on whether the designed controller can effectively compensate the inherent hysteresis phenomenon. In this paper, an adaptive output feedback controller based on a radial basis function neural network (RBFNN) is proposed to eliminate the tracking errors caused by the hysteresis behavior. The observer-based RBFNN is used to online...
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...
This paper focuses on the tracking problem for a class of nonlinearly parameterized (NLP) system with dead-zone input. The nonlinear functional with unknown parameters being nonlinear form is considered without imposing any conditions on unknown parameters. All the dead-zone parameters are unknown. By constructing a novel Lyapunov functional, a simple and smooth adaptive controller is designed via...
This paper concerns the synchronization problem two identical novel hyperchaotic systems with fully unknown parameters. A novel adaptive synchronization controller is realized for the response system to asymptotically synchronize two identical novel hyperchaotic systems. The asymptotic stability of the synchronization error system is guaranteed based on the Lyapunov stability theory and adaptive control...
In this paper, a new adaptive feedback control scheme is proposed for a class of anti-synchronization uncertain time-varying chaotic systems. This adaptive anti-synchronization controller is designed based on Lyapunov stability theory and an analytic expression of the controller with its adaptive laws of parameters is given. The control scheme is successfully applied to two examples: Josephson junction...
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...
In this paper, a new active fault tolerant control strategy is proposed for the plant in the presence of actuator fault and input constraints, which is a combination of a direct adaptive control algorithm with multiple model switching, and the μ-modification is introduced in the model reference control architecture. Based on Lyapunov-Krasovskii stability theory, the stability of overall system is...
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