Discrete Laguerre-based model predictive control for dynamic consensus of a vehicle platoon with time delay

IF 4.6 4区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
R. Resmi, S. Mija, J. Jacob
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引用次数: 3

Abstract

Dynamic consensus of linear time-invariant multi-agent systems (MASs) using distributed model predictive control under the influence of input delay is addressed in this technical note. Model predictive control (MPC) is well suited to solve the consensus problem with its ability to handle multivariable systems and constraints. However, the increased computational complexity of MPC restricts its area of applications. An attempt to bridge this gap is made by proposing a Laguerre-based MPC design to bring down the computational load and make it viable for implementation. The effect of input delay on consensus is examined and the stability margin of a MAS with input delay is computed using the location of the closed-loop poles. A comparison of the proposed algorithm with conventional MPC establishes its superiority in convergence time, robustness to input delay and smoothness of the trajectories. The effectiveness of the proposed design is validated through the simulation of dynamic consensus on the benchmark problem of platoon configuration of vehicles. Abbreviations DLQR: discrete linear quadratic regulator; DMPC: distributed model predictive control; LMI: linear matrix inequality; LTI: linear time invariant; SISO: single-input single-output; MAS: multi-agent system; MIMO: multi-input multi-output; MPC: model predictive control
时滞车队动态一致性的离散Laguerre模型预测控制
本技术说明讨论了在输入延迟影响下使用分布式模型预测控制的线性时不变多智能体系统(MAS)的动态一致性。模型预测控制(MPC)具有处理多变量系统和约束的能力,非常适合解决一致性问题。然而,MPC计算复杂性的增加限制了其应用领域。为了弥补这一差距,提出了一种基于拉盖尔的MPC设计,以降低计算负载并使其可行。研究了输入延迟对一致性的影响,并使用闭环极点的位置计算了具有输入延迟的MAS的稳定裕度。将所提出的算法与传统MPC进行比较,证明了其在收敛时间、对输入延迟的鲁棒性和轨迹的平滑性方面的优势。通过对车队配置基准问题的动态一致性仿真,验证了所提设计的有效性。缩写DLQR:离散线性二次型调节器;DMPC:分布式模型预测控制;LMI:线性矩阵不等式;LTI:线性时不变;SISO:单输入单输出;MAS:多智能体系统;MIMO:多输入多输出;MPC:模型预测控制
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来源期刊
International Journal of Systems Science
International Journal of Systems Science 工程技术-计算机:理论方法
CiteScore
8.00
自引率
9.30%
发文量
164
审稿时长
7.7 months
期刊介绍: International Journal of Systems Science (IJSS) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers that contribute to the methodology and practice in emerging systems engineering themes of intelligence, autonomy and complexity. Modern systems are becoming more and more complex and sophisticated in their demand for performance, reliability and increasing autonomy. Historically, highly analytic and numeric-based methods have sufficed, frequently simplifying the problem to allow analytical tractability. Many manufactured and natural systems (biological, ecological and socio-economic) cannot be adequately represented or analyzed without requiring multiple interacting and interconnected frameworks and a common information-processing framework. A wide range of new theories, methodologies and techniques are required to ‘enable’ such systems, and thus engineering and integration to deal with these demands. IJSS therefore encourages original submissions in these areas, with special focus on papers that are strongly novel as well as not being overly applied. Proposals for special issues in cutting-edge areas of systems science are encouraged, and should be discussed with the Editor-in-Chief. Papers that cover those topics related to operations management and logistics will not be accepted for publication in IJSS. Instead they should be submitted directly to sister journal International Journal of Systems Science: Operations & Logistics. Queries regarding submissions can be made by contacting the Editor-in-Chief, whose decision is final.
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