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1.
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   

2.
This paper addresses a novel fuzzy adaptive control method for a class of uncertain nonlinear multi-input multi-output (MIMO) systems with unknown dead-zone outputs and immeasurable states. The immeasurable states under consideration are estimated by designing a fuzzy state observer. Based on the properties of the Nussbaum-type function, the difficulty of fuzzy adaptive control caused by the unknown dead zone outputs of MIMO nonlinear uncertain systems is overcome. The presented design algorithm not only guarantees that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, but also ensures that the outputs of the MIMO system converge to a small neighborhood of the desired outputs. The main contributions of this research lie in that the developed MIMO systems are more general, and an efficient design method of output-feedback controller is investigated for the studied MIMO systems, which is more applicable in practical environment. Simulation results illustrate the effectiveness of the proposed scheme.  相似文献   

3.
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   

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.
A global decentralized low-complexity tracker design methodology is proposed for uncertain interconnected high-order nonlinear systems with unknown high powers. It is assumed that interconnected nonlinearities are bounded by completely unknown nonlinearities, rather than, a linear combination of high-ordered state variables. Compared with the existing decentralized results for interconnected nonlinear systems with known high powers, the decentralized robust controller, which achieves the pre-designable transient and steady-state tracking performance for each subsystem, is designed by employing nonlinear error surfaces with time-varying performance functions, regardless of unknown nonlinear interactions and high powers related to virtual and actual control variables. The proposed decentralized continuous robust low-complexity tracker is realized without the use of any adaptive or function approximation techniques for estimating unknown parameters and nonlinearities. The stability and preassigned tracking performance of the resulting decentralized low-complexity control system are thoroughly analyzed in the Lyapunov sense. Finally, simulation results on coupled underactuated mechanical systems are provided to show the effectiveness of the proposed theoretical result.  相似文献   

6.
The current paper addresses the fuzzy adaptive tracking control via output feedback for single-input single-output (SISO) nonlinear systems in strict-feedback form. Under the situation of system states being unavailable, the system output is used to set up the state observer to estimate the real system states. Furthermore, the estimation states are employed to design controller. During the control design process, fuzzy logic systems (FLSs) are used to model the unknown nonlinearities. A novel observer-based finite-time tracking control scheme is proposed via fuzzy adaptive backstepping and barrier Lyapunov function approach. The suggested fuzzy adaptive output feedback controller can force the output tracking error to meet the pre-specified accuracy in a fixed time. Meanwhile, all the closed-loop variables are bounded. Compared to some existing finite-time output feedback control schemes, the developed control strategy guarantees that the settling time and the error accuracy are independent of the uncertainties and can be specified by the designer. At last, the effectiveness and feasibility of the proposed control scheme are demonstrated by two simulation examples.  相似文献   

7.
This paper investigates adaptive finite-time practical consensus protocols for a class of second-order multiagent systems with a positive odd power, nonsymmetric input dead zone and uncertain dynamics under a directed communication topology. In this study, three major steps are employed to address the existence of the positive odd power, nonsymmetric input dead zone and uncertain dynamics. Overall, based on the technique of adding one power integrator, useful preliminary results are obtained by configuring a suitable fraction power. Furthermore, to circumvent input dead-zone nonlinearity, an adaptive fuzzy logic (FL) method is used to estimate the width of the dead zone. Finally, the difficulty in designing finite-time practical consensus protocols for the multiagent systems with uncertain dynamics is handled by using radial basis function neural networks (RBFNNs) to approximate the related unknown nonlinear functions. Then, given some reasonable assumptions, it is shown that finite-time practical consensus of the second-order multiagent systems is obtained by using the proposed distributed control protocols and adaptive laws. In addition, the proper approach for selecting parameters is provided such that the neighborhood position error and parameter estimate errors for each agent converge to predesigned small regions of the origin in a finite time. The effectiveness of the developed algorithm is finally validated through a numerical simulation.  相似文献   

8.
This paper proposes an adaptive dynamic surface controller for uncertain time-delay non-strict nonlinear systems with unknown control direction and unknown dead zone. To this end, the problem of uncertainty in nonlinear terms of the overall system is managed such that the estimation of these terms is obtained by applying a fuzzy logic, which is established based on an adaptive approach. A particular observer is then designed to approximate the immeasurable states. Furthermore, to overcome the delay issue in the system, the Lyapunov Krasovskii functional is used to achieve design conditions for dynamic surface control. Moreover, the breach of the output in the system is addressed by employing a Barrier Lyapunov Function. Then, with the aim of the designed controller, the stability of the closed-loop system is ensured such that all states are limited, and the errors are semi-globally uniformly ultimately bounded (SGUUB). Finally, as an illustration of the effectiveness of the proposed controller, a practical simulation is provided.  相似文献   

9.
This paper studies the event-triggered consensus control problem for high-order uncertain nonlinear multi-agent systems with actuator saturation. By using a smooth Lipschitz function to approximate the saturation nonlinearity, an augment system and the Nussbaum function are adopted to deal with the residual terms of saturation nonlinearity based on adaptive backstepping method. Since excessive energy and communication resources will be consumed during the procedure to handle actuator saturation, two event-triggered mechanisms are proposed to save the communication resources and reduce the controllers’ update frequency. Whenever the triggered conditions are satisfied, the control signals transmitted to the actuators are updated and broadcasted to the neighboring area. A ’disturbance-like’ term is integrated so that the event-triggered control problem with actuator saturation can be transformed into a robust problem while the unknown disturbances are tackled by adaptive update laws. Moreover, the requirement for global communication topology known by all the agents is relaxed by introducing new estimators. All the signals in the closed-loop system are uniformly bounded and the consensus tracking errors are exponentially converged to a bounded set. Meanwhile, the Zeno behavior is excluded. Simulation results are employed to validate the advantages of our proposed methods.  相似文献   

10.
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   

11.
The tracking problem of high-order nonlinear multi-agent systems (MAS) with uncertainty is solved by designing adaptive sliding mode control. During the tracking process, node failures are possible to occur, a new agent replaces the failed one. Firstly, a distributed nonsingular terminal sliding mode(NTSM) control scheme is designed for the tracking agents. A novel continuous function is designed in the NTSM to eliminate the singularity and meanwhile guarantee the estimation of finite convergence time. Secondly, the unknown uncertainties in the tracking agents are compensated by proposing an adaptive mechanism in the NTSM. The adaptive mechanism adjusts the control input through estimating the derivative bound of the unknown uncertainties dynamically. Thirdly, the tracking problem with node failures and agent replacements is further investigated. Based on the constructed impulsive-dependent Lyapunov function, it is proved that the overall system will track the target in finite time even with increase of jump errors. Finally, comparison simulations are conducted to illustrate the effectiveness of proposed adaptive nonsingular terminal sliding mode control method for tracking systems suffering node failures.  相似文献   

12.
This paper proposes a new adaptive region tacking control scheme with nonlinear error transformation for underwater vehicles based on barrier Lyapunov functions. In the new scheme, a redefinition of the tracking error is given by introducing nonlinear error transformation in prescribed performance control. Although the results created by the new scheme indicate a slight decrease in the tracking precision, the real tracking error will be still kept within the prescribed performance functions, while the control signals also become smoother, compared with the original prescribed performance control scheme. Then an approximation form of the control input with constraints, together with an improved Nussbaum function, is designed to derive the control law for underwater vehicles with thruster saturation and dead zone. Furthermore, a new velocity error variable is given by introducing an auxiliary variable to compensate the effect from thruster saturation. Finally, it is proved that the nonlinear system is semi-global practical finite-time stable and the tracking error is always kept within the prescribed boundaries. The effectiveness of the proposed region tracking control scheme is validated through simulation-based case studies on an underwater vehicle with measurement noise.  相似文献   

13.
A robust low-complexity design methodology is presented for global tracking of uncertain high-order nonlinear systems with unknown time-varying delays. In contrast to the existing literature, this paper assumes that nonlinear bounding functions of time-delay nonlinearities and high powers of virtual and actual control variables are unknown. Furthermore, a delay-independent tracking scheme using nonlinearly transformed error surfaces is simply designed without the knowledge of nonlinear bounding functions of model nonlinearities, the adaptive technique, and the calculation of repeated time derivatives of certain signals. Thus, the proposed tracker is implemented with low complexity. It is recursively shown that the tracking error is preserved within the predefined bounds of transient and steady-state performance in the Lyapunov sense.  相似文献   

14.
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   

15.
This paper investigates the state-feedback stabilization problem in the smooth case for a class of high-order nonlinear systems with time delays. By generalizing a novel radial basis function neural network (RBF NN) approximation approach to high-order nonlinear systems, we successfully remove the power order restriction and the growth conditions on system nonlinearities. It should be pointed out that the knowledge of NN nodes and weights does not need to be known a priori and operate on-line, and the adaptive parameter is only one. Furthermore, without imposing any growth assumptions on system nonlinearities, we construct a smooth adaptive state-feedback controller which guarantees the closed-loop system to be semi-globally uniformly ultimately bounded (SGUUB). Finally, we apply the proposed scheme to a single-link robot system and a numerical example to demonstrate the effectiveness of the controller.  相似文献   

16.
In this paper, an adaptive distributed control protocol is proposed for non-affine multi-agent system with nonlinear dead-zone input and state constraints under the condition of directed topology. In order to overcome the difficulties caused by non-affine terms in the system, the nonlinear dynamics system is transformed. Then, the neural network technology is introduced to approximate the unknown non-affine terms for the obtained system. State constraints and dead-zone input are common system problems. In order to solve these problems, the barrier Lyapunov function is introduced in this paper. According to the barrier Lyapunov function and backstepping method, an adaptive distributed controller is designed, so that state variables do not violate constraint bounds and the system is not affected by dead-zone input. By Lyapunov stability theory, it is proved that the signals of each follower are cooperative semi-global uniform ultimate boundedness (CSUUB), and the outputs of the followers track the output of the leader. Simulation example is given to demonstrate the effectiveness of the proposed method.  相似文献   

17.
This paper presents an improved adaptive design strategy for neural-network-based event-triggered tracking of uncertain strict-feedback nonlinear systems. An adaptive tracking scheme based on state variables transmitted from the sensor-to-controller channel is designed via only single neural network function approximator, regardless of unknown nonlinearities unmatched in the control input. Contrary to the existing multiple-function-approximators-based event-triggered backstepping control results with multiple triggering conditions dependent on all error surfaces, the proposed scheme only requires one triggering condition using a tracking error and thus can overcome the problem of the existing results that all virtual controllers with multiple function approximators should be computed in the sensor part. This leads to achieve the structural simplicity of the proposed event-triggered tracker in the presence of unmatched and unknown nonlinearities. Using the impulsive system approach and the error transformation technique, it is shown that all the signals of the closed-loop system are bounded and the tracking error is bounded within pre-designable time-varying bounds in the Lyapunov sense.  相似文献   

18.
This paper studies the adaptive tracking control problem for a class of uncertain high-order fully actuated (HOFA) systems with actuator faults and full-state constraints. Firstly, we design a novel nonlinear transformation function (NTF) only related to state and constraint boundaries and capable of handling asymmetric time-varying constraints. With the designed function, we obtain an equivalent totally unconstrained HOFA model which is generally simpler to design controllers than first-order state-space model. Then, the adaptive fault-tolerant controller is constructed with the help of the HOFA approach. By applying the Lyapunov stability theory, it is rigorously proved that the output tracking error converges to zero asymptotically, other signals of the resulting closed-loop systems are bounded, and full-state constraints are not violated for all time. Finally, the simulation results verify the efficiency of the proposed control design method.  相似文献   

19.
This article proposes a novel explicit-time and explicit-accuracy adaptive fuzzy control for a state-constrained nonlinear nonstrict-feedback uncertain system. This method can explicitly parameterize the upper bound of settling-time with low initial control input under a bounded initial condition. Meanwhile, this method can also explicitly parameterize the upper bound of accuracy while achieving low control input based on the adaptive fuzzy dynamic-approximation theorem. Firstly, a novel generalized explicit-time stability system is proposed by introducing the boundary gain term to render the time-parameter explicit, this method can solve the input conservatism problem caused by the unbounded-state gain term of traditional fixed/prdefined-time function. Then, according to the universal fuzzy approximation theorem, the novel dynamic relationship of adaptive fuzzy logic system between approximation error and adaptive parameters is presented. This relationship can lead to the adaptive fuzzy dynamic-approximation theorem, and an adaptive law designed by this theorem can realize the Lyapunov stability of adaptive control system under a Lasalle invariant set. In the end, a novel adaptive fuzzy control scheme is proposed by the generalized explicit-time function and adaptive fuzzy dynamic-approximation theorem. This scheme can achieve the explicit-time stability by the human-like activation function, and the accuracy can be parameterized by Lyapunov synthesis. Compared with other existing fixed/prdefined-time adaptive fuzzy control methods, the proposed explicit-time and explicit-accuracy controller achieves a significant reduction in the initial control input. Theoretical analysis and simulation results validate the effectiveness of the proposed method.  相似文献   

20.
针对一类不确定非线性时滞系统,提出了一种具有确定逼近域的自适应模糊控制器的设计方案。在动态面控制（DSC）的基础上,通过时滞代换技巧,使得自适应模糊逼近器的输入为参考信号,从而可以明确定义逼近域,同时可以处理系统中完全未知的时滞信号。基于Lyapunov-Krasovskii范函,证明闭环系统所有信号为半全局一致有界的,并且跟踪误差可以收敛到原点附件的一个小邻域内。仿真结果进一步说明了该方法的有效性。  相似文献   

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