Weisheng Yan

Distributed receding horizon control of constrained nonlinear vehicle formations with guaranteed γ -gain stability

This paper investigates the distributed receding horizon control (RHC) problem of a vehicle platoon with nonlinear dynamics and subject to system constraints, where each vehicle can communicate with its immediate predecessor and follower. A novel optimization problem and detailed distributed RHC algorithm are designed in order to keep a platoon formation, and further to ensure neighbor γ -gain stability (which is a new notion proposed in this paper and generalizes the string stability). The sufficient conditions on ensuring closed-loop stability and neighbor γ -gain stability are established, respectively. Finally, simulation studies are provided to verify the theoretical results. It is shown that it is possible to achieve certain control performance (i.e.,? γ -gain stability) and keep a formation simultaneously for the nonlinear vehicle platoon using distributed RHC.

On Neighbor Information Utilization in Distributed Receding Horizon Control for Consensus-Seeking

This paper investigates the issue on how to utilize neighbor information in the distributed receding horizon control (RHC)-based consensus problem for first-order multiagent systems. The distributed RHC-based consensus problem is first formulated in a general framework in terms of using neighbor information. Based on the framework, a sufficient condition on utilizing neighbor information to ensure consensus is developed for the finite horizon case. For the infinite horizon case, a necessary and sufficient condition is proposed, and the best way of using neighbor information to achieve fastest convergence rate is also presented. It is shown that: 1) the way of utilizing neighbor information plays an important role in reaching consensus; 2) the parameter that ensures consensus is related with the network topology; and 3) the best convergence rate in consensus can be attained if the neighbor information is appropriately utilized. Simulation studies verify the proposed theoretical results.

Mutual Information-Based Multi-AUV Path Planning for Scalar Field Sampling Using Multidimensional RRT*

Autonomous underwater vehicles (AUVs) have been widely employed in ocean survey, monitoring, and search and rescue tasks for both civil and military applications. It is beneficial to use multiple AUVs that perform environmental sampling and sensing tasks for the purposes of efficiency and cost effectiveness. In this paper, an adaptive path planning algorithm is proposed for multiple AUVs to estimate the scalar field over a region of interest. In the proposed method, a measurable model composed of multiple basis functions is defined to represent the scalar field. A selective basis function Kalman filter is developed to achieve model estimation through the information collected by multiple AUVs. In addition, a path planning method, the multidimensional rapidly exploring random trees star algorithm, which uses mutual information, is proposed for the multi-AUV system. Employing the path planning algorithm, the sampling positions of the AUVs are determined to improve the quality of future samples by maximizing the mutual information between the scalar field model and observations. Extensive simulation results are provided to demonstrate the effectiveness of the proposed algorithm. Additionally, an indoor experiment using four robotic fishes is carried out to validate the algorithms presented.

Continuous-time model predictive control of under-actuated spacecraft with bounded control torques

The stabilization problem of rigid spacecraft is essential for space explorations and operations. This paper studies the model predictive stabilization problem of a class of underactuated rigid spacecrafts with two bounded control torques. A novel model predictive control (MPC) algorithm is designed by making use of the homogeneity of the system dynamics. In addition, a local homogeneous Lyapunov function is constructed based on which the approach to designing the terminal set and other parameters are developed. Finally, the conditions for ensuring algorithm feasibility and closed-loop stability are provided. We show that under the given conditions, the designed MPC algorithm is feasible, and the closed-loop system is asymptotically stable. Simulation and comparison studies verify that the developed results are effective and valid, and the designed controller fulfills the constraint satisfaction and achieves much faster convergence rate in comparison with conventional continuous time-varying controllers.

Receding horizon control based consensus scheme in general linear multi-agent systems

This paper investigates the consensus problem of general linear multi-agent systems under the framework of optimization. A novel distributed receding horizon control (RHC) strategy for consensus is proposed. We show that the consensus protocol generated by the unconstrained distributed RHC can be expressed in an explicit form. Based on the resulting consensus protocol the necessary and sufficient conditions for ensuring consensus are developed. Furthermore, we specify more detailed consensus conditions for multi-agent systems with general and one-dimensional linear dynamics depending on Riccati difference equations (RDEs), respectively. Finally, a case study verifies the proposed scheme and the corresponding theoretical results.

Periodic event-triggering in distributed receding horizon control of nonlinear systems

How to efficiently use limited system resources in distributed receding horizon control (DRHC) is an important issue. This paper studies the DRHC problem for a class of dynamically decoupled nonlinear systems under the framework of event-triggering, to efficiently make use of the computation and communication resources. To that end, a distributed periodic event-triggered strategy is designed and a detailed DRHC algorithm is presented. The conditions for ensuring feasibility of the designed algorithm and stability of the closed-loop system are developed, respectively. We show that the closed-loop system is input-to-state stable if the energy bound of the disturbances, the triggering condition and the cooperation matrices fulfill the proposed conditions.

A leader-follower formation control strategy for AUVs based on line-of-sight guidance

In order to resolve the formation tracking problem of cooperative control of multiple Autonomous Underwater Vehicles (AUVs), a variable structure control law was proposed to keep the AUVs track along the predefined trajectory by minimizing the cross track error, which is calculated from the line-of-sight angle. Furthermore, a mathematical model for the formation based on leader-follower was established and the relative formation control strategy based on feedback linearization was derived. Simulation results show that the proposed approach is feasible and the effect of formation tracking can be expressed visually.

Sensorless direct torque controlled drive of brushless DC motor based on fuzzy logic

Investigations were carried out on a sensorless fuzzy direct torque control (DTC) which drives brushless DC motors (BLDC). It is deduced that the amplitude of stator flux linkage can not been controlled in BLDC-DTC since it is automatically determined by every 60 electrical degrees commutation. Then, the control of the flux linkage is unused in the proposed system. For the sake of improving the static and dynamic performance of the system, fuzzy logic is introduced into the system, which the torque error and flux linkage angle of BLDC were all properly fuzzified into several subsets to accurately select the voltage space vector in order to smooth the torque and quicken the torque response. A state observer is designed to estimate the back-EMF, the torque and rotor speed can be derived from the estimated back-EMF. Simulations illustrate the operation and performance of the proposed scheme.

Cooperative localization with communication delays for MAUVs

In this paper, we consider the problem of Cooperative Localization(CL) with communication delays for Multiple Autonomous Underwater Vehicles(MAUVs). Localization is a crucial cycle for long range navigation of MAUVs. In the Leader-follower cooperative structure, one master AUV is equipped with high precision navigation system, and several slaver AUVs are equipped with low precision navigation system. To sharing information, inter-vehicle communication is becoming an important requirement for Cooperative Localization. However, due to the terrible underwater environment, acoustic communication is still a difficult challenge for AUVs until now. Taking into account the communication delays, a Delayed Extended Kalman Filter (DEKF) for Cooperative Localization is designed, where the delayed messages were converted to current after some useful transformations. At the end of this paper, simulation results are provided to prove the superiority and practicality of the proposed DEKF algorithm.

Time-optimal coverage control for multiple unicycles in a drift field

This paper is concerned with the time-optimal coverage control problem for multiple unicycles in a drift field. Regarding the optimal time for each vehicle to reach an arbitrary point in the given region as a metric, a novel cost function is defined to evaluate the performance of the coverage network. Then, the time-optimal Voronoi partition is developed by using the optimal control theory and Lloyds algorithms. On this basis, a distributed coverage control law is proposed to deploy the unicycles to the optimal positions. The stability of this coverage system is further analyzed. Finally, numerical simulations are provided to illustrate the effectiveness of the proposed approaches.