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This paper considers an optimal bipartite formation control problem for high-order nonlinear multiagent systems (MASs) with the consideration of obstacle/collision avoidance. Contrary to existing literature, the control strategy designed in this paper can render the agents in a bipartite formation to complete the obstacle/collision avoidance tasks without requiring the obstacles to be located on the coordinate axis. To save resources, an identifier-critic-actor-based optimized formation control scheme is designed for MASs. An obstacle/collision avoidance approach based on dynamical systems (DS) is designed for high-order nonlinear MASs. Different from the existing related results, the proposed DS-based obstacle/collision avoidance approach can avoid the phenomenon that the control quantities approach infinity near obstacles or other agents, and eliminate the dependence on global information. Finally, a simulation example is given to validate the proposed control method. [ABSTRACT FROM AUTHOR]

This paper investigates fixed-time tracking consensus problem for high-order nonlinear multi-agent systems (MASs) with actuator faults and performance constraint. Different from existing results that focus on first/second/high-order MASs with integral structure, the investigated MASs involve complex nonlinear dynamics with each agent being modeled as high-order non-strict-feedback form. That is, unknown nonlinear function appears in every state component equation of each subsystem, and contains all the states of the corresponding subsystem. Due to the adverse effects from complex nonlinear dynamics, the previous methods may be unavailable, which motivates the work. To address the problems arising from unknown nonlinear dynamics and actuator faults, fuzzy systems and robust technique are employed. Meanwhile, the performance constraints on the tracking errors can be ensured by appropriately utilizing barrier Lyapunov functions and graph theory. Furthermore, power integrator technique incorporated with Lyapunov functions is used to guarantee the property of fixed time convergence. It is shown that, by using the proposed control strategy, despite the presence of high-order complex nonlinear dynamics and actuator faults, the tracking consensus errors can converge into a neighborhood around zero within fixed time. In addition, the tracking consensus performance can be guaranteed during the whole operation, and all the signals in MASs are bounded. Finally, the effectiveness of the proposed control strategy has been proved by rigorous stability analysis and two simulation examples. [ABSTRACT FROM AUTHOR]

In this paper, the problem of adaptive actor-critic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper concerns the H ∞ filtering of Markov jump nonlinear systems with general uncertain transition probabilities allowed to be uncertain and unknown. Attention is focused on the construction of an extended filter such that the filtering error system is stochastically stable with a prescribed H ∞ performance requirement. Effective strategies are developed to deal with nonlinearities induced by uncertain and unknown transition probabilities and system nonlinearities, which is also the main contribution of this work. Based on these strategies, sufficient conditions to render the filtering error systems stochastic stable with the prescribed H ∞ performance are established in the framework of linear matrix inequalities. The validity of the proposed filtering scheme is illustrated by numerical examples. [ABSTRACT FROM AUTHOR]