This article attempts to realize zero-error constrained tracking for hypersonic flight vehicles (HFVs) subject to unknown control directions and asymmetric flight state constraints. The main challenges of reaching such goals consist in that addressing multiple unknown control directions requires novel conditional inequalities encompassing the summation of multiple Nussbaum integral terms, and in that the summation of conditional inequality may be bounded even when each term approaches infinity individually, but with opposite signs. To handle this challenge, novel Nussbaum functions that are designed in such a way that their signs keep the same on some periods of time are incorporated into the control design, which not only ensures the boundedness of multiple Nussbaum integral terms but preserves that velocity and altitude tracking errors eventually converge to zero. Fuzzy-logic systems (FLSs) are exploited to approximate model uncertainties. Asymmetric integral barrier Lyapunov functions (IBLFs) are adopted to handle the fact that the operating regions of flight state variables are asymmetric in practice, while ensuring the validity of fuzzy-logic approximators. Comparative simulations validate the effectiveness of our proposed methodology in guaranteeing convergence, smoothness, constraints satisfaction, and in handling unknown control directions.

This article aims to realize event-triggered constrained consensus tracking for high-order nonlinear multiagent networks subject to full-state constraints. The main challenge of achieving such goals lies in the fact that the standard designs [e.g., backstepping, event-triggered control, and barrier Lyapunov functions (BLFs)] successfully developed for low-order dynamics fail to work for high-order dynamics. To tackle these issues, a novel high-order event-triggered mechanism is devised to update the actual control input, lowering the communication and computation burden. More precisely, compared with the conventional event-triggered mechanism, not only the amplitudes of control signals and a fixed threshold are considered but a monotonically decreasing function is introduced to allow a relatively big threshold, while guaranteeing consensus tracking error to be small. Then, a high-order tan-type BLF working for both constrained and unconstrained scenarios is incorporated into the distributed adding-one-power-integrator design for the purpose of confining full states within some compact sets all the time. A finite-time convergent differentiator (FTCD) is introduced to circumvent the ``explosion of complexity.'' The consensus tracking error is shown to eventually converge to a residual set whose size can be adjusted as small as desired through choosing appropriate design parameters. Comparative simulations have been conducted to highlight the superiorities of the developed scheme.

This paper studies distributed singularity-free finite-time consensus tracking control for quite a large class of high-order (powers are positive odd integers) nonlinear multi-agent networks in the presence of unknown asymmetric dead zone. Achieving finite-time consensus tracking for such dynamics is extremely challenging because feedback linearization and backstepping methods successfully developed for low-order systems fail to work, and some appropriate exponential terms typically arising from finite-time stability are difficult to design due to the existence of high powers and strong couplings among distinct agents. To this purpose, an adding-one-power-integrator methodology is skillfully incorporated into the finite-time stability theory so as to stabilize the closed-loop system. Over the course of design, a variable-separable lemma is utilized to extract the unknown asymmetric dead-zone input in a “linear-like” manner and fuzzy logic systems are utilized to estimate the unknown system continuous nonlinearities over some compact sets. The singularity issue typical of finite-time control is overcome by delicately introducing a switching function. It is rigorously proved that the consensus tracking error eventually converges to a residual set, whose size can be made as small as desired, in finite time, while guaranteeing the boundedness of all closed-loop signals. Comparative simulations are finally provided to verify the effectiveness of the presented scheme on the existing control methods.