Jie Lan

Ethyl 2-methyl-2,3-butadienoate acts as a 1,4-dipole synthon and undergoes [4 + 2] annulation with N-tosylimines in the presence of an organic phosphine catalyst. The resulting adducts, ethyl 6-substituted-1-(4-tosyl)-1,2,5,6-tetrahydro-pyridine-3-carboxylates, are formed in excellent yields with complete regioselectivity. Mechanistic reasoning for this new annulation has led to an expansion of the reaction scope by employing ethyl 2-(substituted-methyl)-2,3-butadienoates to give ethyl 2,6-cis-disubstituted-1-(4-tosyl)-1,2,5,6-tetrahydro-pyridine-3-carboxylates with high diastereoselectivities.

This article addresses a distributed time-varying optimal formation protocol for a class of second-order uncertain nonlinear dynamic multiagent systems (MASs) based on an adaptive neural network (NN) state observer through the backstepping method and simplified reinforcement learning (RL). Each follower agent is subjected to only local information and measurable partial states due to actual sensor limitations. In view of the distributed optimized formation strategic needs, the uncertain nonlinear dynamics and undetectable states may jointly affect the stability of the time-varying cooperative formation control. Furthermore, focusing on Hamilton-Jacobi-Bellman optimization, it is almost incapable of directly dealing with unknown equations. Above uncertainty and immeasurability processed by adaptive state observer and NN simplified RL are further designed to achieve desired second-order formation configuration at the least cost. The optimization protocol can not only solve the undetectable states and realize the prescribed time-varying formation performance on the premise that all the errors are SGUUB, but also prove the stability and update the critics and actors easily. Through the above-mentioned approaches offer an optimal control scheme to address time-varying formation control. Finally, the validity of the theoretical method is proven by the Lyapunov stability theory and digital simulation.

The 2-azaphenalenyl radical 2 has been synthesized and characterized by ESR spectroscopy. Variable-temperature ESR measurements were carried out on both the phenalenyl (1) and the 2-azaphenalenyl (2) radicals. The phenalenyl radical 1 has the known propensity to dimerize at temperatures below 20 degrees C, but unexpectedly less so than originally reported. The first experimental measurement of bond dissociation enthalpy for the dimerization of the phenalenyl radical 1 was obtained in CCl(4) (11.34 +/- 0.11 kcal/mol) and toluene (9.8 +/- 0.7 kcal/mol). The 2-azaphenalenyl radical 2 does not show a propensity to dimerize over the measurable temperature range (220-330 K), but does so in the presence of Cu(hfac)(2) (hfac = hexafluoroacetylacetonate). The latter complex was characterized by X-ray crystallography.

This article presents an adaptive fuzzy fixed time time-varying formation control (TVFC) method for uncertain heterogeneous nonlinear multiagent systems (HNMASs) with full state constraints. Meanwhile, both partial loss of effectiveness and bias fault are considered in HNMASs. The fuzzy logic systems are selected as an effective tool to approximate uncertain nonlinear functions. The original constrained states of the systems will be converted to unconstrained states by the nonlinear transformed function. Compared with previous papers, it is the first time to handle the TVFC problem of HNMASs with full state constraints. In addition, formation control based on an adaptive fuzzy fixed time strategy not only ensures fast convergence of the system, but also the convergence time doesn't depend on any initial conditions. The stability of HNMAs is proven by the fixed time stability theory. Finally, a simulation is given to testify the effectiveness of the control method.

This article proposes an adaptive fuzzy controller for a class of uncertain strict-feedback nonmatching nonlinear single-input single-output systems with fuzzy dead zone and full time-varying state constraints. The states considered here are immeasurable and full states of the systems are constrained in a bounded set with time-varying regions. Following the adaptive backstepping design framework, the tangent barrier Lyapunov functions are introduced to the integrated design to address the problems in such systems. Fuzzy logic systems are used to identify the unknown smooth functions and unknown parameters. An input-driven observer is designed to estimate the immeasurable states. To distinguish the conventional deterministic dead zone models, the output of dead zone is uncertainty. The form of indeterminate dead zone as a combination of a liner and a disturbance-like term is extended by the fuzzy algorithms. Even though the output of dead zone is fuzzy and adopting the integrated design, the proposed fuzzy controller can ensure that all the signals in the closed-loop systems are semiglobal uniformly ultimately bounded and guarantee the tracking performance. Finally, simulation results are shown to verify the effectiveness and reliability of the proposed approach.