379 research outputs found
Transients of platoons with asymmetric and different Laplacians
We consider an asymmetric control of platoons of identical vehicles with
nearest-neighbor interaction. Recent results show that if the vehicle uses
different asymmetries for position and velocity errors, the platoon has a short
transient and low overshoots. In this paper we investigate the properties of
vehicles with friction. To achieve consensus, an integral part is added to the
controller, making the vehicle a third-order system. We show that the
parameters can be chosen so that the platoon behaves as a wave equation with
different wave velocities. Simulations suggest that our system has a better
performance than other nearest-neighbor scenarios. Moreover, an
optimization-based procedure is used to find the controller properties
Robust Distributed Control Protocols for Large Vehicular Platoons with Prescribed Transient and Steady State Performance
In this paper, we study the longitudinal control problem for a platoon of
vehicles with unknown nonlinear dynamics under both the predecessor-following
and the bidirectional control architectures. The proposed control protocols are
fully distributed in the sense that each vehicle utilizes feedback from its
relative position with respect to its preceding and following vehicles as well
as its own velocity, which can all be easily obtained by onboard sensors.
Moreover, no previous knowledge of model nonlinearities/disturbances is
incorporated in the control design, enhancing in that way the robustness of the
overall closed loop system against model imperfections. Additionally, certain
designer-specified performance functions determine the transient and
steady-state response, thus preventing connectivity breaks due to sensor
limitations as well as inter-vehicular collisions. Finally, extensive
simulation studies and a real-time experiment conducted with mobile robots
clarify the proposed control protocols and verify their effectiveness.Comment: IEEE Transactions on Control Systems Technology, accepte
Research on Information Flow Topology for Connected Autonomous Vehicles
Information flow topology plays a crucial role in connected autonomous vehicles (CAVs). It describes how CAVs communicate and exchange information with each other. It predominantly affects the platoon\u27s performance, including the convergence time, robustness, stability, and scalability. It also dramatically affects the controller design of CAVs. Therefore, studying information flow topology is necessary to ensure the platoon\u27s stability and improve its performance. Advanced sliding mode controllers and optimisation strategies for information flow topology are investigated in this project.
Firstly, the impact of information flow topology on the platoon is studied regarding tracking ability, fuel economy and driving comfort. A Pareto optimal information flow topology offline searching approach is proposed using a non-dominated sorting genetic algorithm (NSGA-II) to improve the platoon\u27s overall performance while ensuring stability.
Secondly, the concept of asymmetric control is introduced in the topological matrix. For a linear CAVs model with time delay, a sliding mode controller is designed to target the platoon\u27s tracking performance. Moreover, the Lyapunov analysis is used via Riccati inequality to guarantee the platoon\u27s internal stability and input-to-output string stability. Then NSGA-II is used to find the homogeneous Pareto optimal asymmetric degree to improve the platoon\u27s performance. A similar approach is designed for a nonlinear CAVs model to find the Pareto heterogeneous asymmetric degree and improve the platoon\u27s performance.
Thirdly, switching topology is studied to better deal with the platoon\u27s communication problems. A two-step switching topology framework is introduced. In the first step, an offline Pareto optimal topology search with imperfect communication scenarios is applied. The platoon\u27s performance is optimised using a multi-objective evolutionary algorithm based on decomposition (MOEA/D). In the second step, the optimal topology is switched and selected from among the previously obtained Pareto optimal topology candidates in real-time to minimise the control cost. For a continuous nonlinear heterogeneous platoon with actuator faults, a sliding mode controller with an adaptive mechanism is developed. Then, the Lyapunov approach is applied to the platoon\u27s tracking error dynamics, ensuring the systems uniformly ultimately bounded stability and string stability. For a discrete nonlinear heterogeneous platoon with packet loss, a discrete sliding mode controller with a double power reaching law is designed, and a modified MOEA/D with two opposing adaptive mechanisms is applied in the two-step framework.
Simulations verify all the proposed controllers and frameworks, and experiments also test some. The results show the proposed strategy\u27s effectiveness and superiority in optimising the platoon\u27s performance with multiple objectives
Transients of Platoons with Asymmetric and Different Laplacians
We consider an asymmetric control of platoons of identical vehicles with nearest-neighbor interaction. Recent results show that if the vehicle uses different asymmetries for position and velocity errors, the platoon has a short transient and low overshoots. In this paper we investigate the properties of vehicles with friction. To achieve consensus, an integral part is added to the controller, making the vehicle a third-order system. We show that the parameters can be chosen so that the platoon behaves as a wave equation with different wave velocities. Simulations suggest that our system has a better performance than other nearest-neighbor scenarios. Moreover, an optimization-based procedure is used to find the controller properties
Stability Margin Scaling Laws for Distributed Formation Control as a Function of Network Structure
We consider the problem of distributed formation control of a large number of
vehicles. An individual vehicle in the formation is assumed to be a fully
actuated point mass. A distributed control law is examined: the control action
on an individual vehicle depends on (i) its own velocity and (ii) the relative
position measurements with a small subset of vehicles (neighbors) in the
formation. The neighbors are defined according to an information graph.
In this paper we describe a methodology for modeling, analysis, and
distributed control design of such vehicular formations whose information graph
is a D-dimensional lattice. The modeling relies on an approximation based on a
partial differential equation (PDE) that describes the spatio-temporal
evolution of position errors in the formation. The analysis and control design
is based on the PDE model. We deduce asymptotic formulae for the closed-loop
stability margin (absolute value of the real part of the least stable
eigenvalue) of the controlled formation. The stability margin is shown to
approach 0 as the number of vehicles N goes to infinity. The exponent on the
scaling law for the stability margin is influenced by the dimension and the
structure of the information graph. We show that the scaling law can be
improved by employing a higher dimensional information graph.
Apart from analysis, the PDE model is used for a mistuning-based design of
control gains to maximize the stability margin. Mistuning here refers to small
perturbation of control gains from their nominal symmetric values. We show that
the mistuned design can have a significantly better stability margin even with
a small amount of perturbation. The results of the analysis with the PDE model
are corroborated with numerical computation of eigenvalues with the state-space
model of the formation.Comment: This paper is the expanded version of the paper with the same name
which is accepted by the IEEE Transactions on Automatic Control. The final
version is updated on Oct. 12, 201
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