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1.
The leader-following consensus problems for multi-agent systems with a linear and Lipschitz nonlinear dynamics are considered. Distributed adaptive protocols and Lipschitz distributed adaptive protocols are respectively designed for the linear and Lipschitz nonlinear cases, under which leader-following consensus is reached for jointly connected topology. Finally, a simulation example is provided to illustrate the theoretical results.  相似文献   

2.
In this paper, we develop two new model reference adaptive control (MRAC) schemes for a class of nonlinear dynamic systems that is robust with respect to an uncertain state (output) dependent nonlinear perturbations and/or external disturbances with unknown bounds. The design is based on a controller parametrization with an adaptive integral action. Two types of adaptive controllers are considered—the state feedback controller with a plant parameter identifier, and the output feedback controller with a linear observer.  相似文献   

3.
In this paper, an observer-based adaptive control problem for a class of high-order switched nonlinear systems in non-strict feedback form with fuzzy dead zone and arbitrary switchings is investigated. Fuzzy logic system was utilized to model the unknown nonlinear function with the universal approximation ability. An adaptive high-order observer is constructed to estimate unavailable state variables. The effect of dead zone can be eliminated by a Nussbaum function. By using the Lyapunov stability theory and backstepping design procedure, the proposed adaptive controller can guarantee all the variables in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB). Simulation results are exhibited to demonstrate the effectiveness of the proposed control scheme.  相似文献   

4.
Decentralized adaptive neural backstepping control scheme is developed for uncertain high-order stochastic nonlinear systems with unknown interconnected nonlinearity and output constraints. For the control of high-order nonlinear interconnected systems, it is assumed that nonlinear system functions are unknown. It is for the first time to control stochastic nonlinear high-order systems with output constraints. Firstly, by constructing barrier Lyapunov functions, output constraints are handled. Secondly, at each recursive step, only one adaptive parameter is updated to overcome over-parameterization problems, and RBF neural networks are used to identify unknown nonlinear functions so that the difficulties caused by completely unknown system functions and stochastic disturbances are tackled. Finally, based on the Lyapunov stability method, the decentralized adaptive control scheme via neural networks approximator is proposed, ultimately reducing the number of learning parameters. It is shown that the designed controller can guarantee all the signals of the resulting closed-loop system to be semi-globally uniformly ultimately bounded (SGUUB), and the tracking errors for each subsystem are driven to a small neighborhood of zero. The simulation studies are performed to verify the effectiveness of the proposed control strategy.  相似文献   

5.
This article investigates the adaptive regulation problem of uncertain delayed nonlinear systems. Remarkably, the systems have multiple delays in systems’ states and the input, and the nonlinear terms as a whole can belong to one of four different growing conditions. By introducing the dynamic-gain-based transformations, we obtain the new dynamic systems. By using homogeneous domination method, adaptive regulation strategy and by flexibly selecting the dynamic gain, two unified adaptive control methods are presented such that the obtained systems are globally asymptotic stable. Simulation results verify the effectiveness of the methods of this paper.  相似文献   

6.
This paper is concerned with the problem of adaptive disturbance attenuation for a class of nonlinear systems. The traditional adaptive methods are almost impossible to compensate the time-varying unknown disturbance by designing parameter adaptive laws without a priori knowledge about the bounds of external disturbances. To solve the problem, a new strategy is proposed by constructing an augmented system where the external disturbance is considered as another component of the augmented state vector. Based on this, a double-gain nonlinear observer is employed to estimate the state of the augmented nonlinear system. Further, an output feedback control strategy is designed, and it is proved that the proposed strategy ensures that all the signals are bounded and the tracking error exponentially converges to an adjustable compact set. Finally, an example is performed to demonstrate the validity of the proposed scheme.  相似文献   

7.
This study focuses on the research of the globally asymptotic tracking problem of unknown nonlinear reaction-diffusion equations with time-varying coefficients and uncertain external disturbance. Firstly, fuzzy logic systems and adaptive bounding technique are used to deal with nonlinear reaction-diffusion equations with time-varying coefficients and uncertain external disturbance. Secondly, a novel global state feedback adaptive fuzzy control algorithm is proposed to make the nonlinear reaction-diffusion equations track the target systems globally and asymptotically. In addition, the globally asymptotic tracking condition can be obtained, which overcomes the semi-global results in the existing literatures. Finally, three simulation examples are given to illustrate the feasibility and effectiveness of the proposed control protocols.  相似文献   

8.
This paper is concerned with event-triggered adaptive fuzzy tracking control for high-order stochastic nonlinear systems. The approach of fuzzy logic systems (FLSs) approximation is extended to high-order stochastic nonlinear systems to deal with the unknown nonlinear uncertainties. A novel high-order adaptive fuzzy tracking controller is firstly presented via a backstepping approach and event-triggering mechanism which can mitigate the unnecessary waste of computation and communication resources. Based on the above techniques, frequently-used growth assumptions imposed on unknown system nonlinearities are removed and the influence for the high order is handled. The proposed high-order adaptive fuzzy tracking control method not only deals with the influence of high order, but also ensures that the tracking error converges to a small neighborhood of the origin in probability. Finally, the effectiveness of the proposed control method is illustrated by a numerical example.  相似文献   

9.
In this paper, a novel approach for the design of an indirect adaptive fuzzy output tracking excitation control of power system generators is proposed. The method is developed based on the concept of differentially flat systems through which the nonlinear system can be written in canonical form. The flatness-based adaptive fuzzy control methodology is used to design the excitation control signal of a single machine power system in order to track a reference trajectory for the generator angle. The considered power system can be written in the canonical form and the resulting excitation control signal is shown to be nonlinear. In case of unknown power system parameters due to abnormalities, the nonlinear functions appearing in the control signal are approximated using adaptive fuzzy systems. Simulation results show that the proposed controller can enhance the transient stability of the power system under a three-phase to ground fault occurring near the generator terminals.  相似文献   

10.
This paper concerns an adaptive fuzzy tracking control problem for a class of switched uncertain nonlinear systems in strict-feedback form via the modified backstepping technique. The unknown nonlinear functions are approximated by the generalized fuzzy hyperbolic model (GFHM). It is shown that if the designed parameters in the controller and adaptive laws are appropriately selected, then all closed-loop signals are bounded and the stability of the system can be kept under average dwell time methods. In the end, simulation studies are presented to illustrate the effectiveness of the proposed method.  相似文献   

11.
This paper studies the adaptive fuzzy fault-tolerant control design problem for a class of stochastic multi-input and multi-output (MIMO) nonlinear systems in pure-feedback form. The nonlinear systems under study contain unknown functions, unmeasured states and actuator faults, which are described by the loss of effectiveness and lock-in-place modes. With the help of fuzzy logic systems identifying uncertain stochastic nonlinear systems, a fuzzy state observer is established for estimating the unmeasured states. Based on the backstepping design technique with the nonlinear tolerant-fault control theory, an adaptive fuzzy output feedback faults-tolerant control approach is developed. It is proved that the proposed fault-tolerant control approach can guarantee that all the signals of the resulting closed-loop system are bounded in probability. Moreover, the observer errors and tracking errors can be regulated to a small neighborhood of the origin by choosing design parameters appropriately. A simulation example is provided to show the effectiveness of the proposed approach.  相似文献   

12.
An evolutionary programming-based adaptive observer is presented in this paper to improve the performance of state estimation of nonlinear time-varying sampled-data systems. Also, this paper presents a novel state-space adaptive tracker together with the proposed observer and estimation schemes for nonlinear time-varying sampled-data systems having actuator failures. For the class of slowly varying nonlinear time-varying systems, the proposed methodology is able to achieve the desired fault detection and performance recovery for the originally well-designed systems, as long as the controller having the high-gain property. For practical implementation, we utilize the advantages of digital redesign methodology to convert a well-designed high-gain analog controller/observer into its corresponding low-gain digital controller/observer. Illustrative examples are given to demonstrate the effectiveness of the proposed method. The developed digitally redesigned adaptive tracker with the proposed observer and estimator is suitable for implementation by using microprocessors.  相似文献   

13.
In this paper, a novel backstepping-based adaptive dynamic programming (ADP) method is developed to solve the problem of intercepting a maneuver target in the presence of full-state and input constraints. To address state constraints, a barrier Lyapunov function is introduced to every backstepping procedure. An auxiliary design system is employed to compensate the input constraints. Then, an adaptive backstepping feedforward control strategy is designed, by which the tracking problem for strict-feedback systems can be reduced to an equivalence optimal regulation problem for affine nonlinear systems. Secondly, an adaptive optimal controller is developed by using ADP technique, in which a critic network is constructed to approximate the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation. Therefore, the whole control scheme consists of an adaptive feedforward controller and an optimal feedback controller. By utilizing Lyapunov's direct method, all signals in the closed-loop system are guaranteed to be uniformly ultimately bounded (UUB). Finally, the effectiveness of the proposed strategy is demonstrated by using a simple nonlinear system and a nonlinear two-dimensional missile-target interception system.  相似文献   

14.
This paper investigates the adaptive fuzzy control design problem of multi-input and multi-output (MIMO) non-strict feedback nonlinear systems. The considered control systems contain unknown control directions and dead zones. Fuzzy logic systems (FLSs) are utilized to approximate the unknown nonlinear functions, and the state observers are designed to estimate immeasurable states. By constructing a dead zone compensator and introducing a Nussbaum gain function into the backstepping technique, an adaptive fuzzy output feedback control method is developed. The proposed adaptive fuzzy controller is proved to guarantee the semi-globally uniformly ultimately bounded (SGUUB) of the closed-loop system, and can solve the control design problems of unmeasured states, unknown control directions and dead zones. The simulation results are given to demonstrate the effectiveness of the proposed control method.  相似文献   

15.
In this paper, a decentralized adaptive backstepping control scheme is proposed for a class of interconnected systems with nonlinear multisource disturbances and actuator faults. The nonlinear multisource disturbances comprise of two parts: one is the time-varying parameterized uncertainty; the other is the dynamic unexpected signal formulated by a nonlinear exogenous system. For each subsystem, the disturbances are compensated by an adaptive controller based on several dynamic signals and the bound estimation approach. Moreover, the effect of the actuator faults is tackled in spite of the fact that the faults may change in different cases infinite times. Meanwhile, through several smooth functions, the interactions among the subsystems are successfully disposed. As a result, the tracking errors can converge to an arbitrarily small value by choosing the design parameters appropriately. The proof of the closed-loop system stability is completed. Several illustrative examples are employed to demonstrate the effectiveness of the proposed method.  相似文献   

16.
In this paper, a novel error-driven nonlinear feedback technique is designed for partially constrained errors fuzzy adaptive observer-based dynamic surface control of a class of multiple-input-multiple-output nonlinear systems in the presence of uncertainties and interconnections. There is no requirements that the states are available for the controller design by constructing fuzzy adaptive observer, which can online identify the unmeasurable states using available output information only. By transforming partial tracking errors into new error variables, partially constrained tracking errors can be guaranteed to be confined in pre-specified performance regions. The feature of the error-driven nonlinear feedback technique is that the feedback gain self-adjusts with varying tracking errors, which prevents high-gain chattering with large errors and guarantees disturbance attenuation with small errors. Based on a new non-quadratic Lyapunov function, it is proved that the signals in the resulted closed-loop system are kept bounded. Simulation and comparative results are given to demonstrate the effectiveness of the proposed method.  相似文献   

17.
In this paper, the tracking control problem of a class of uncertain strict-feedback nonlinear systems with unknown control direction and unknown actuator fault is studied. By using the neural network control approach and dynamic surface control technique, an adaptive neural network dynamic surface control law is designed. Based on the neural network approximator, the uncertain nonlinear dynamics are approximated. Using the dynamic surface control technique, the complexity explosion problems in the design of virtual control laws and adaptive updating laws can be overcome. Moreover, to solve the unknown control direction and unknown actuator fault problems, a type of Nussbaum gain function is incorporated into the recursive design of dynamic surface control. Based on the designed adaptive control law, it can be confirmed that all of the signals in the closed-loop system are semi-global bounded, and the convergence of the tracking error to the specified small neighborhood of the origin could be ensured by adjusting the designing parameters. Finally, two examples are provided to demonstrate the effectiveness of the proposed adaptive control law.  相似文献   

18.
The adaptive asymptotic tracking control problem for a class of stochastic non-strict-feedback switched nonlinear systems is addressed in this paper. For the unknown continuous functions, some neural networks are used to approximate them online, and the dynamic surface control (DSC) technique is employed to develop the novel adaptive neural control scheme with the nonlinear filter. The proposed controller ensures that all the closed-loop signals remain semiglobally bounded in probability, at the same time, the output signal asymptotically tracks the desired signal in probability. Finally, a simulation is made to examine the effectiveness of the proposed control scheme.  相似文献   

19.
The focus of this paper is on the detection and estimation of parameter faults in nonlinear systems with nonlinear fault distribution functions. The novelty of this contribution is that it handles the nonlinear fault distribution function; since such a fault distribution function depends not only on the inputs and outputs of the system but also on unmeasured states, it causes additional complexity in fault estimation. The proposed detection and estimation tool is based on the adaptive observer technique. Under the Lipschitz condition, a fault detection observer and adaptive diagnosis observer are proposed. Then, relaxation of the Lipschitz requirement is proposed and the necessary modification to the diagnostic tool is presented. Finally, the example of a one-wheel model with lumped friction is presented to illustrate the applicability of the proposed diagnosis method.  相似文献   

20.
The decentralized tracking control methods for large-scale nonlinear systems are investigated in this paper. A backstepping-based robust decentralized adaptive neural H∞ tracking control method is addressed for a class of large-scale strict feedback nonlinear systems with uncertain disturbances. Under the condition that the nonlinear interconnection functions in subsystems are unknown and mismatched, the decentralized adaptive neural network H∞ tracking controllers are designed based on backstepping technology. Neural networks are used to approximate the packaged multinomial including the unknown interconnections and nonlinear functions in the subsystems as well as the derivatives of the virtual controls. The effect of external disturbances and approximation errors is attenuated by H∞ tracking performance. Whether the external disturbances occur or not, the output tracking errors of the close-loop system are guaranteed to be bounded. A practical example is provided to show the effectiveness of the proposed control approach.  相似文献   

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