Bin He

Bio: Bin He is an academic researcher. The author has contributed to research in topics: Control theory (sociology) & Consensus. The author has an hindex of 3, co-authored 3 publications receiving 48 citations.

Neural-network-based sliding-mode control for multiple rigid-body attitude tracking with inertial information completely unknown

Abstract: This paper addresses the multiple rigid bodies attitude tracking control problem in presence of inertial information completely unknown. In order to attenuate the effect of unknown parameters, the neural networks technology is employed to approximate the unknown nonlinear terms derived from the controller design procedure. Based on lumped tracking errors between neighbors, a novel sliding-mode control protocol is proposed and an approximate expression of inverse matrix is also applied to avoid possible singular phenomenon. The Lyapunov theory is applied to guarantee that all signals in the closed-loop system are uniformly ultimately bounded and that all rigid-body attitude synchronize to the desired trajectory with bounded residual errors. Compared with prior works, the dynamics of each rigid-body discussed here is more general and does not require the assumption linearity in the unknown parameters or the matching condition. Moreover, the bounded residual errors can be reduced as small as desired by selected suitable parameters. Simulation results demonstrate the effectiveness of the proposed method.

The consensus region design and analysis of fractional-order multi-agent systems

Abstract: The consensus problem of fractional-order multi-agent systems is studied in this paper. To achieve consensus, a fractional-order observer-type consensus protocol based on relative output measurements is proposed and its stability is also certified theoretically. The notion of consensus region for fractional-order dynamic is introduced and analysed. A multistep consensus protocol design procedure is presented for given consensus region. Several numerical simulations are given to demonstrate the effectiveness of the theoretical results.

Sliding mode learning control for T‐S fuzzy system and an application to hypersonic flight vehicle

Abstract: Sliding mode‐based learning control is presented for T‐S fuzzy system. A T‐S fuzzy model with both uncertainties and unmodeled dynamics is proposed firstly, in which the information of uncertainties and unmodeled dynamics are assumed to be unknown. Then, according to a given reference model, state‐tracking error system is built. Respecting facts, the input matrices of the built T‐S fuzzy model are different from each other. An extended state observer is built for estimating the unknown uncertainties and unmodeled dynamics, and a corresponding sliding surface is proposed. A learning controller is then presented for the closed loop system. Moreover, a numerical simulation result on hypersonic flight vehicles is considered to testify the controller's availability.

The consensus region design and analysis of fractional-order multi-agent systems

Abstract: This paper addresses the consensus region design and analysis problem of fractional-order multi-agent systems, where time-invariant communication topology consisting of general linear node is considered. To achieve consensus, a fractional-order observer-type consensus protocol based on relative output measurements is proposed. The notion of consensus region for fractional-order dynamic is introduced and analyzed. The consensus region can be designed by an observer-type protocol if and only if each agent is stabilizable and detectable. A multi-step consensus protocol design procedure is presented for given consensus region. Several numerical simulations are given to demonstrate the effectiveness of the theoretical results.

Combined active learning Kriging with optimal saturation nonlinear vibration control for uncertain systems with both aleatory and epistemic uncertainties

Abstract: This paper addresses the vibration control problems of uncertain systems with both random and multidimensional parallelepiped (MP) convex variables by uniting the optimal saturation nonlinear control (OSNC) and an active learning Kriging (ALK) method. This method can be named ALK-MP-OSNC. The dynamic equations of the controlled systems can be written in ODE forms, and the functions containing saturation nonlinearities on the right side of each of ODE equation can be approximately replaced via using the Kriging model. The efficiency of the Kriging model can be improved through combining the differential evolution (DE) global optimal algorithm with the distance constraint condition. A three-pendulum system, a satellite motion and a moving-mass beam system are employed to demonstrate the performance of the improved ALK-MP-OSNC. Results indicates that the proposed method can efficiently drive the uncertain pendulum system to a chaotic behavior and the other two uncertain systems to a periodic motion. The efficiency and the accuracy of the proposed method can be researched through comparing with the original ALK and the Monte Carlo simulation. In conclusion, the proposed method can be applied to complex engineering fields such as aerospace engineering, civil engineering, ocean engineering, and space deployable engineering.

Distributed nonlinear control algorithms for network consensus

Abstract: In this short note, we point out a mistake existing in the proof of Theorem 3.1 in Hui and Haddad (2008).

Distributed Consensus Control of One-Sided Lipschitz Nonlinear Multiagent Systems

Abstract: This paper addresses the distributed consensus controller design approaches for one-sided Lipschitz nonlinear multiagents by employing relative state feedback. A new treatment for one-sided Lipschitz nonlinearity is rendered from the consensus control point of view. By employing the quadratic inner-boundedness and the one-sided Lipschitz constraints, a sufficient condition for asymptotic consensus of nonlinear systems under strongly connected communication topologies is provided. Further, a robust consensus protocol design scheme for the nonlinear multiagents is derived by ensuring the ${L_{2}}$ stability of the consensus error system. Furthermore, a novel robust consensus control scheme against amplitude-bounded perturbations is developed that guarantees asymptotic convergence of the consensus error into a compact set. Extensions to the proposed methodologies for the leader-following consensus for a spanning tree communication topology with the leader as the root are addressed. In contrast to the conventional consensus control methodologies, this paper is less conservative and can be applied to a broader class of nonlinear multiagent systems. Moreover, the proposed consensus control approach is less conservative for robustness against disturbances owing to its ability to handle amplitude-bounded disturbances and due to the relaxation of a balanced communication topology. A numerical simulation study is provided for the consensus control of eight mobile agents.

Distributed finite-time fault-tolerant containment control for multiple ocean Bottom Flying node systems with error constraints

Abstract: The Ocean Bottom Flying Node (OBFN) belongs to Autonomous Underwater Vehicle (AUV) designed for detecting seabed resources. When considering model uncertainties, external disturbances, and thruster faults, by applying the nonsingular fast terminal sliding-mode technique, a distributed finite-time fault-tolerant error constraint containment control method for multiple OBFN systems is proposed under directed communication topology. Besides, only a part of follower OBFNs can get the information of leader OBFNs. First, the error constraint strategy is considered to improve the system performance while the defined error variable of containment control was converted into a suitable form. Then, by choosing the appropriate nonsingular fast terminal sliding surface, the systems states can reach the sliding surface in finite time such that the follower OBFNs could converge to the convex hull formed by the leader OBFNs in finite time. Neural Network (NN) is employed to estimate and compensate the general disturbances consisting of model uncertainties, external disturbances, and thruster faults. An adaptive law is designed to compensate the upper bound of the estimation errors. The finite-time stability of the systems and the boundedness of containment errors are proved by utilizing graph theory, finite time theory, and Lyapunov technique. Numerical simulations under different types of thruster faults are given to show the effectiveness of the proposed methods.

Coordination of fractional-order nonlinear multi-agent systems via distributed impulsive control

Abstract: The coordination of fractional-order nonlinear multi-agent systems via distributed impulsive control method is studied in this paper. Based on the theory of impulsive differential equations, algebr...