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Because of strong coupling, nonlinear, and time-varying characteristics, it is difficult to control complex spacecraft. By means of combining with controlled object dynamics and performance requirements, characteristic modeling and control approach is an effective way to solve this problem. Aimed at the flexible satellites described by using characteristic modeling approach, with the help of fuzzy...
The ability of Vertical and/or Short Take-Off and Landing is the objective of advanced fighter and shipboard fighter. In this paper we proposed a prototype of tailless configured STOVL aerial vehicle. Based on which, the mathematical model was studied by mechanical analysis and CFD (Computing Fluid Dynamics) computation. Besides, an intelligent adaptive based control law was proposed and the optimization...
Power control is the most important system requirement for code-division multiple-access (CDMA) wireless cellular communication systems. This paper presents a robust adaptive power controller for CDMA systems with unmodeled dynamics and bounded disturbances. Modified least-squares scheme with a relative dead zone is developed to form a novel robust adaptive control algorithm, without much prior knowledge...
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.
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...
We investigate the learning issue in the robust adaptive neural-network (NN) control process of manipulator with unknown system dynamics and disturbance. Based on recently developed deterministic theory, the regression vector of an appropriately designed robust adaptive NN controller satisfies the partial persistent exciting (PE) condition when tracking a periodic or periodic-like reference orbit,...
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...
In this paper, a novel adaptive neural network control scheme is put forward for a class of SISO nonlinear systems with backlash-like hysteresis, where the hysteresis is modeled by a differential equation in the presence of bounded external disturbances. By using the merit of tangent function and the method of minimal parameterization, the proposed designs need no requirements for the knowledges of...
Distributed robust adaptive control is investigated for a class of stochastic multi-agent systems with unknown time-varying structure parameters, unmodeled dynamics, external disturbances, and interactions among agents. The control goal is to make the states of all the agents converge to a desired function of the population state average (PSA). Due to the fact that only local information is available...
An adaptive dynamic surface control scheme is designed to achieve output tracking for a class of nonlinear output feedback system with uncertain actuator failure pattern, value and time instants. State observer is used to estimate unavailable plant states. Detailed stability analysis is carried out to prove the uniform ultimate boundedness of all closed-loop system signals.
This paper presents a novel design of adaptive sliding mode observer. An adaptive sliding mode observer with a proportional and integral sliding surface is derived and the stability condition of the closed-loop system is established. The proposed adaptive sliding mode observer could reconstruct the unmeasured states and estimate unknown system parameters in real time despite parameter variations and...
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...
To expand the initial angle condition in stabilizing the double inverted pendulum, the adaptive Human-Simulated Intelligent Controller is proposed. Based on it, the phase plane is divided into tow blocks according to requirement of control performance. Within the zero block the integration action works; Outside the zero block the adaptive fuzzy PD works. This control structure, called after adaptive...
In this paper, it is showed that if neural networks are used as feedforward compensators instead of feedback ones, then we can ensure the global stability of closed-loop systems and determine the neural network approximation domain via the bound of known reference signals. It should be pointed out that this domain is very important for designing the neural network structure, for example, it directly...
In this paper, the development of an innovative nonlinear controller for looper and tension control in hot strip finishing mills is traced based on sliding mode and adaptive control. First, the sliding mode approach is applied in the angle loop to compensate disturbances and unmodeled dynamics. Then, an adaptive feedback controller is used in the tension loop to improve the performance of the overall...
Piezoelectric actuators are popularly applied in precision positioning mechanism in Scanning Tunneling Microscope due to its advantage of nanometer resolution. Accurate tracking is difficult to be achieved owing to the intrinsic nonlinear hysteresis of piezoelectric ceramics. An adaptive control scheme combining neural network with traditional PID controller is proposed to improve the performance...
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...
Three kinds of approximators are widely used in adaptive controllers for the nonlinear systems with uncertainty. They are neural network, fuzzy logic systems and wavelet approximator, respectively. By unifying these three approximators, we developed an on-line approximation based controller for a class of uncertain nonlinear systems. It is proved that with the proposed control law and update laws,...
The performance of robust adaptive control system based on traditional revised algorithm is awful in the presence of unmodeled dynamics and the performance will go bad, even be unstable, when the working condition (including the parameter, reference input, and so on) change. This paper designs the multiple models robust adaptive controller to control the discrete single-variable non-minimum phase...
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