Application of ℒ1 Adaptive Controller for the Design of a Novel Decentralized Leader Follower Formation Algorithm

Kumaresan, G.; Kale, Alexander

doi:10.1016/j.ifacol.2016.03.139

Cited by 8 publications

(6 citation statements)

References 10 publications

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“…surge/cruise), payload and vehicle sizes. Furthermore, L 1 AC has been used to augment an LQR baseline controller to enhance the performance tracking enhancement of a decentralised leader-follower coordination scheme for unmanned aerial vehicles [42]. While receiving great attention in aerospace applications, there are many attractive opportunities for the L 1 AC architecture in smart-grid applications.…”

Section: Decentralised Baseline Voltage Controlmentioning

confidence: 99%

“…Local DC-DC boost power converters are equipped with decentralised state-feedback (DeSSf) baseline controllers and augmented with L 1 adaptive voltage controllers. The rationale for implementing an augmentation approach as opposed to a fully adaptive one is that in real systems it is common to have baseline controllers designed to provide reference tracking and disturbance rejection during nominal operation [37,38,42]. This approach can also facilitate greater flexibility to a system owner as previously discussed.…”

Section: Introductionmentioning

confidence: 99%

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A Distributed Scalable Architecture using L1 Adaptive Controllers for Primary Voltage Control of DC Microgrids

O'Keeffe,

Riverso,

Albiol-Tendillo

et al. 2018

Preprint

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This paper proposes a new distributed control architecture for distributed generation units in heterogeneous DC islanded microgrids. Each unit is equipped with state-feedback baseline and augmenting L1 adaptive voltage controllers at the primary level of the microgrid control hierarchy. Local controller synthesis is scalable as it only requires information about corresponding units, couplings, and at most, the addition of state-predictor measurements of neighbouring controllers. Global asymptotic stability of the microgrid is guaranteed in a plug-and-play fashion by exploiting Lyapunov functions and algebraic Riccati equations. The performance of the proposed architecture is evaluated using a heterogeneous DC islanded microgrid that consists of 6 DC-DC boost converters configured in a radial and meshed topology. The use of L1 adaptive controllers achieves fast and robust microgrid voltage stability in the presence of plug-and-play operations, topology changes and unknown load changes. Finally, the distributed architecture is tested on a bus-connected islanded-microgrid consisting of linear resistive load and non-linear DC motor.

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Section: Decentralised Baseline Voltage Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Distributed Scalable Architecture using L1 Adaptive Controllers for Primary Voltage Control of DC Microgrids

O'Keeffe,

Riverso,

Albiol-Tendillo

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Centralised L 1 AC architectures have been notably successful in safety-critical applications including; sub-scale NASA aircraft auto-pilots [34], manned aircraft [35], and unmanned water/aerial vehicles [36,37]. In addition to our decentralised [28] and distributed [29] L 1 AC architectures, decentralised schemes were formulated in [38,39], and were implemented to augment aircraft baseline controllers [40]. Unlike [34][35][36][37][38][39][40], we consider unmatched interconnections and provide robustness to constant disturbances via integral action.…”

Section: Decentralised L 1 Adaptive Primary Voltage Controlmentioning

confidence: 99%

“…In addition to our decentralised [28] and distributed [29] L 1 AC architectures, decentralised schemes were formulated in [38,39], and were implemented to augment aircraft baseline controllers [40]. Unlike [34][35][36][37][38][39][40], we consider unmatched interconnections and provide robustness to constant disturbances via integral action.…”

Section: Decentralised L 1 Adaptive Primary Voltage Controlmentioning

confidence: 99%

Decentralised L1 Adaptive Primary Controllers and Distributed Consensus-Based Secondary Control for DC Microgrids with Constant-Power Loads

O'Keeffe,

Riverso,

Albiol-Tendillo

et al. 2018

Preprint

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Constant-power loads are notoriously known to destabilise power systems, such as DC microgrids, due to their negative incremental impedance. This paper equips distributed generation units with decentralised L1 adaptive controllers at the primary level of the microgrid control hierarchy. Necessary and sufficient conditions are provided to local controllers for overall microgrid stability when constant-power loads are connected. The advantages of the architecture over conventional heuristic approaches are: (i) scalable design, (ii) plug-and-play functionality, (iii) well defined performance and robustness guarantees in a heterogeneous and uncertain system, and (iv) avoids the need for online measurements to obtain non-a priori system impedance information. The proposed primary control architecture is evaluated with distributed consensus-based secondary level controls using a bus-connected DC microgrid, which consists of DC-DC buck and boost converters, linear and non-linear loads. Stability of the overall hierarchical control system is proven using a unit-gain approximation of the primary level.

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“…12 A novel L 1 adaptive-based control method has been investigated by augmenting a fixed gain linear quadratic regulator control for leader-follower-based decentralized formation flying. 13 A leader-follower faulttolerant formation control method has been studied to let follower UAVs converge into the convex hull when there are only a part of follower UAVs can obtain the reference information from the leader UAV. 14 Although fruitful results on leader-follower formation problems can be found in recent publications, there is still a lot of space for further investigation such as finite-time problems.…”

Section: Introductionmentioning

confidence: 99%

Iterative learning-based formation control for multiple quadrotor unmanned aerial vehicles

Zhao

Jing

Chen

et al. 2020

International Journal of Advanced Robotic Systems

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A double-layer formation control is proposed to solve the repeated tasks for multiple quadrotor unmanned aerial vehicle systems. The first layer aims at achieving a formation target in which the iterative learning control is designed based on relative distance with neighbor unmanned aerial vehicles and absolute distance with virtual leader unmanned aerial vehicle. The formation controller is responsible for keeping the formation shape and generating the desired flying trajectories for each drones. The second layer control aims at achieving a high-precision tracking to desired flying trajectories which are generated from the formation controller. A double closed-loop proportional-derivative strategy is designed to ensure the accuracy of trajectory tracking for each individual drone. Simulations for the circle formation mission of the multiple quadrotor unmanned aerial vehicle system are given to verify the efficiency of the proposed method.

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Application of ℒ1 Adaptive Controller for the Design of a Novel Decentralized Leader Follower Formation Algorithm

Cited by 8 publications

References 10 publications

A Distributed Scalable Architecture using L1 Adaptive Controllers for Primary Voltage Control of DC Microgrids

A Distributed Scalable Architecture using L1 Adaptive Controllers for Primary Voltage Control of DC Microgrids

Decentralised L1 Adaptive Primary Controllers and Distributed Consensus-Based Secondary Control for DC Microgrids with Constant-Power Loads

Iterative learning-based formation control for multiple quadrotor unmanned aerial vehicles

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