Existing Nussbaum function based results on consensus of multi-agent systems require that the unknown control directions all agents should be same. This note proposes an adaptive method to relax such a requirement allow non-identical directions, under condition some are known. Technically, novel idea is proposed construct new function, from which conditional inequality developed handle time-varying input gains. Then, integrated with technique for each agent adaptively updated. Moreover, in...

Reinforcement learning (RL) has been successfully employed as a powerful tool in designing adaptive optimal controllers. Recently, off-policy emerged to design controllers for systems with completely unknown dynamics. However, current approaches tracking control either result bounded error, rather than zero or require partial knowledge of the system Moreover, they usually collect large set data learn solution. To obviate these limitations, this paper applies combination and experience-replay...

As the Internet services spread all over world, many kinds and a large number of security threats are increasing. Therefore, intrusion detection systems, which can effectively detect accesses, have attracted attention. This paper describes novel fuzzy class-association-rule mining method based on genetic network programming (GNP) for detecting intrusions. GNP is an evolutionary optimization technique, uses directed graph structures instead strings in algorithm or trees programming, leads to...

To achieve an excellent dual-arm coordination of the humanoid robot, it is essential to deal with nonlinearities existing in system dynamics. The literatures so far on robot control have a common assumption that problem output hysteresis could be ignored. However, practical applications, widely spread; and its limits motion/force performances robotic system. In this paper, adaptive neural scheme, which takes unknown computational efficiency into account, presented investigated. controller...

This paper presents a saturated Nussbaum function based approach for robotic systems with unknown actuator dynamics. To eliminate the effect of control shock from traditional function, new type is developed idea time-elongation. Moreover, by exploiting properties proposed promising theorem established to deal multiple nonlinearities. In what follows, integrated adaptive technique such that stability analysis system completed. It thus guarantees state asymptotically converges desired...

In this article, we address the bearing-only formation control problem of 3-D networked robotic systems with parametric uncertainties. The contributions article are two-fold: 1) bearing-rigid theory is extended to solve nonlinear Euler-Lagrange-like model and 2) a novel almost global stable distributed law proposed for systems. Specifically, subject nonholonomic constraints dynamics first transformed into model. By exploring graph theory, backstepping approach used design controller....

This paper proposes an adaptive fuzzy asymptotic control method for multiple input output (MIMO) nonlinear systems with unknown coefficients, a focus on handling nonlinearities and directions. For all the existing Nussbaum gain-based approaches, it is difficult to investigate coefficients problem since time-varying disturbances coexist should be simultaneously tackled in stability analysis. To overcome above difficulty, we propose robust approach of MIMO systems. Benefiting from proposed...

In this article, we investigate the optimal output tracking problem for linear discrete-time systems with unknown dynamics using reinforcement learning (RL) and robust regulation theory. This only allows to utilize outputs of reference system controlled system, rather than their states, differs from most existing works that depend on state system. The is formulated into a quadratic by proposing family dynamic controllers. Then, it shown solving equivalent equations, whose solution, however,...

Cooperative control of multiagent systems (MAS) on communication networks has received a great deal attention, mostly for the case homogeneous agents, which all have same dynamics. An advantage cooperative synchronization mechanisms is their local distributed nature, makes them scalable to large networks. However, most existing design require some global information, such as leader's dynamics or graph so that protocols are technically not fully distributed. Moreover, nature susceptible...

In this article, we consider the resilience problem in presence of communication faults encountered distributed secondary voltage and frequency control an islanded alternating current microgrid. Such include partial failure links some classes data manipulation attacks. This practical important yet challenging issue has been taken into limited consideration by existing approaches, which commonly assume that measurement or between generations (DGs) is ideal satisfies restrictive assumptions....

Due to the fact that backlash nonlinearity is widespread in actuators, it impossible ignore its existence and achieve excellent desirable mechanical system performance. In this paper, problem of humanoid robot grasping a common object with unknown actuator investigated. To tackle nonsmooth nonlinearity, smooth adaptive inverse incorporated compensate line-segment effect. Moreover, decentralized robust fuzzy control constructed developed guarantee object's motion internal forces converge...

This paper presents an asymptotic tracking control design method for stochastic strict-feedback systems via fuzzy logic systems. In the existing results, controls are usually limited to be bounded in probability. However, how realize remains a dilemma. achieves by proposing novel gain suppressing inequality approach. Specifically, three-part construction is performed achieve such objective First, technique developed lay foundation carrying out Lyapunov stability analysis. Second, integrated...

Obtaining high-accuracy vehicle localization is essential for safe navigation in automated vehicles, however, complex urban environments result inaccurate positioning because of multipath and non-line-of-sight errors, making precise an important unsolved problem. Different from conventional model-based approaches which require rigid assumptions on sensors noise models, data-driven artificial intelligent can provide new solutions Global Navigation Satellite System (GNSS) problems...