This article focuses on finite-time adaptive fuzzy output-feedback control for a class of nontriangular nonlinear systems with full-state constraints and unmeasurable states. Fuzzy-logic systems and the fuzzy state observer are employed to approximate uncertain nonlinear functions and estimate the unmeasured states, respectively. In order to solve the algebraic loop problem generated by the nontriangular structure, a variable separation approach based on the property of the fuzzy basis function is utilized. The barrier Lyapunov function is incorporated into each step of backstepping, and the condition of the state constraint is satisfied. The dynamic surface technique with an auxiliary first-order linear filter is applied to avoid the problem of an “explosion of complexity.” Based on the finite-time stability theory, an adaptive fuzzy controller is constructed to guarantee that all signals in the closed-loop system are bounded, the tracking error converges to a small neighborhood of the origin in a finite time, and all states are ensured to remain in the predefined sets. Finally, the simulation results reveal the effectiveness of the proposed control design.

This paper addresses an adaptive fuzzy finite-time control for a class of uncertain strict-feedback nonlinear systems with backlash-like hysteresis and stochastic disturbances. At first, a novel semi-globally finite-time stability in probability (SGFSP) criterion is established based on Lyapunov function method. Based on the proposed stability criterion, an adaptive fuzzy finite-time control scheme is designed. In the design process of the controller, command filter is introduced to improve the traditional adaptive finite-time control based on the backstepping method, which can avoid the problems of “explosion of complexity” and “singularity”. Meanwhile, via constructing the corresponding error compensating systems, the effect of errors generated by the command filters is reduced, such that the original systems have more better tracking performance. To cope with the effect of backlash-like hysteresis input, an auxiliary system is constructed, in which the output signal is applied to compensate the effect of the hysteresis. Under the proposed control scheme, the tracking error can converge to a small neighborhood of original in finite-time, and the closed-loop system is SGFSP. Finally, the effectiveness of the proposed control strategy is further verified by two simulation examples

The cooperative bipartite containment control problem of linear multiagent systems is investigated based on the adaptive distributed observer in this article. The graph among the agents is structurally balanced. A novel distributed error term is designed to guarantee that some outputs of the followers converge to the convex hull spanned by the leaders, and the other followers' outputs converge to the symmetric convex hull. The matrices of the exosystems are not available for each follower. A general method is presented to verify the validity of a novel distributed adaptive observer rather than the previous approach. In other words, the definition of the M-matrix is not necessary in our result. Based on the distributed adaptive observer, an output-feedback control protocol is designed to solve the bipartite containment control problem. Finally, a numerical simulation is given to illustrate the effectiveness of the theoretical results.

This article focuses on the adaptive bipartite containment control problem for the nonaffine fractional-order multi-agent systems (FOMASs) with disturbances and completely unknown high-order dynamics. Different from the existing finite-time theory of fractional-order system, a lemma is developed that can be applied to actualize the aim of finite-time bipartite containment for the considered FOMASs, in which the settling time and convergence accuracy can be estimated. Via applying the mean-value theorem, the difficulty of the controller design generated by the nonaffine nonlinear term is overcome. A neural network (NN) is employed to approximate the ideal input signal instead of the unknown nonaffine function, then a distributed adaptive NN bipartite containment control for the FOMASs is developed under the backstepping structure. It can be proved that the bipartite containment error under the proposed control scheme can achieve finite-time convergence even though the follower agents are subjected to completely unknown dynamic and disturbances. Finally, the feasibility and validity of the obtained results are exhibited by the simulation examples.

In this paper, the finite-time containment control problem of the nonlinear multi-agent systems (MAS) is investigated, in which the follower agents are subjected to full state constraints. The fuzzy logic system is employed to approximate the uncertain dynamic of the nonlinear MAS. A new nonlinear transformation function (NTF) is proposed, which serves as a unified tool for coping with the systems subjected to state constraints and no constraint. By combing the variable transformation with the proposed NTF, the original systems with state constraints are converted into the equivalent free-constrained systems. Moreover, as long as the boundedness of the states in transformed systems is guaranteed, the states of the original MAS don't transgress the preassigned boundaries. Based on the finite-time stability theory, the adaptive fuzzy control scheme is constructed for the transformed systems. It is proved that the outputs of all the followers are driven to converge to the convex hull spanned by the leaders in finite time, and all the signals in the closedloop systems are bounded in sense of mean square. The full state constraints for the followers are not violated all the time. Specially, the control structure does not need to change even there is no constraint imposes on the state. Finally, simulation examples are given to verify the effectiveness of the proposed finite-time control scheme.

This article addresses an adaptive fuzzy control for the nonstrict-feedback nonlinear systems with asymmetric time-varying full state constraints. To prevent the state constraints being violated, the nonlinear state-dependent function (NSDF) is introduced instead of the tradition barrier lyapunov function (BLF). The constrained systems are transformed into a novel free-constrained systems based on the NSDF. A direct approach is given to cope with the state constraints. Fuzzy logic system is utilized to approximate the uncertain nonlinear system functions. The new affine variables are constructed for the transformed systems, and the prior knowledge of the control gains is not required necessarily. Under the designed control scheme, the boundedness of the signals in the closed-loop systems is guaranteed certainly, and the asymmetric time-varying constraints are maintained. This proposed method removes the feasibility condition on the virtual controller derived from the method of BLF. The effectiveness of the proposed control strategy is verified by two simulation examples.