•A novel string stability criterion by dividing a mixed vehicular platoon into multiple interconnected sub-systems.•A practical string stability criterion for a mixed vehicular platoon over ...predominant acceleration frequency boundaries.•A new CAV control strategy incorporating human-driven vehicles’ car following characteristics.•A new CAV control strategy to stabilize mixed vehicular platoons with guaranteed feasibility.
This paper presents a car-following control strategy of connected automated vehicles (CAVs) to stabilize a mixed vehicular platoon consisting of CAVs and human-driven vehicles. This study first establishes a string stability criterion for a mixed vehicular platoon. Specifically, a mixed vehicular platoon is decomposed into “subsystems” that are all possible sequential subsets of the platoon. String stability is then defined as the “head-to-tail” string stability for all subsystems: the magnitude of a disturbance is not amplified from the first vehicle to the last vehicle of each subsystem. Based on this definition, distributed frequency-domain-based CAV control is proposed to increase the number of head-to-tail string stable subsystems and consequently dampen stop-and-go disturbances drastically. Specifically, an H-infinity control problem is formulated, where the maximum disturbance “damping ratios” in each subsystem is minimized within the predominant acceleration frequency boundaries of human-driven vehicles. Simulation experiments, embedded with real human-driven vehicle trajectories, were conducted, and results show that the proposed control can effectively dampen stop-and-go disturbances.
Safety is the foremost concern for autonomous platooning. The vehicle-to-vehicle (V2V) communication delays and the sudden appearance of obstacles will trigger the safety of the intended ...functionality (SOTIF) issues for autonomous platooning. This research proposes a holistic robust motion controller framework (MCF) for an intelligent and connected vehicle platoon system. The MCF utilizes a hierarchical structure to resolve the longitudinal string stability and the lateral control problem under the complex driving environment and time-varying communication delays. Firstly, the H-infinity feedback controller is developed to ensure the robustness of the platoon under time-varying communication delay in the upper-level coordination layer (UCL). The output from UCL will be delivered to the lower-level motion-planning layer (LML) as reference signals. Secondly, the model predictive control (MPC) algorithm is implemented in the LML to achieve multi-objective control, which comprehensively considers the reference signals, the artificial potential field, and multiple vehicle dynamics constraints. Furthermore, three critical scenarios are co-simulated for case studies, including platooning under time-varying communication delay, merging, and obstacle avoidance scenarios. The simulation results indicate that, compared with single-structure MPC, the proposed MCF can offer a better suppression on position error propagation, and get improvements on maximum position error in the three scenarios by 19.2%, 59.8%, and 15.3%, respectively. Lastly, the practicability and effectiveness of the proposed MCF are verified via the hardware-in-the-loop experiment. The average conducting time of the proposed method on the Speedgoat real-time target machine is 1.1 milliseconds, which meets the real-time requirements.
Accurate estimation of state-of-charge (SoC) is vital to safe operation and efficient management of lithium-ion batteries. Currently, the existing SoC estimation methods can accurately estimate the ...SoC in a certain operation condition, but in uncertain operating environments, such as unforeseen road conditions and aging related effects, they may be unreliable or even divergent. This is due to the fact that the characteristics of lithium-ion batteries vary under different operation conditions and the adoption of constant parameters in battery model, which are identified offline, will affect the SoC estimation accuracy. In this paper, the joint SoC estimation method is proposed, where battery model parameters are estimated online using the H-infinity filter, while the SoC are estimated using the unscented Kalman filter. Then, the proposed method is compared with the SoC estimation methods with constant battery model parameters under different dynamic load profiles and operation temperatures. It shows that the proposed joint SoC estimation method possesses high accuracy, fast convergence, excellent robustness and adaptability.
In this paper we consider L∞-algebras equipped with complete descending filtrations. We prove that, under some mild conditions, an L∞ quasi-isomorphism U:L→L˜ induces a weak equivalence between the ...Deligne–Getzler–Hinich (DGH) ∞-groupoids corresponding to L and L˜, respectively. This paper may be considered as a modest addition to foundational paper 10 by Ezra Getzler.
Among Zeno paradoxes the most known are Dichotomy, Achilles, Arrow, and Stadium. These argumentations state that movement is impossible since it is not thinkable. According to the ascendant form of ...dichotomy, a mobile cannot touch its destination since it always must to reach the half of the distance. The solutions of Diogenes, Aristotle and mathematical analysis are not satisfactory. Finally, the difference between rest and movement can be only conventionally established.
The paper deals with the theory of potentials with respect to the
α
-Riesz kernel |
x
−
y
|
α
−
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of order
α
∈ (0,2 on
ℝ
n
,
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3
. Focusing first on the inner
α
-harmonic measure
ε
y
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(
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being ...the unit Dirac measure at
y
∈
ℝ
n
, and
μ
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the inner
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-Riesz balayage of a Radon measure
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to
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arbitrary), we describe its Euclidean support, provide a formula for evaluation of its total mass, establish the vague continuity of the map
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↦
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outside the inner
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-irregular points for
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, and obtain necessary and sufficient conditions for
ε
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to be of finite energy (more generally, for
ε
y
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to be absolutely continuous with respect to inner capacity) as well as for
ε
y
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(
ℝ
n
)
≡
1
to hold. Those criteria are given in terms of newly defined concepts of inner
α
-thinness and inner
α
-ultrathinness of
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at infinity that for
α
= 2 and
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Borel coincide with the concepts of outer 2-thinness at infinity by Doob and Brelot, respectively. Further, we extend some of these results to
μ
A
general by verifying the integral representation formula
μ
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=
∫
ε
y
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d
μ
(
y
)
. We also show that for every
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⊂
ℝ
n
, there exists a
K
σ
-set
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0
⊂
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such that
μ
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=
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for all
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arbitrary, thereby strengthening Fuglede’s result established for
A
Borel (Acta Math., 1960). Being new even for
α
= 2, the results obtained also present a further development of the theory of inner Newtonian capacities and of inner Newtonian balayage, originated by Cartan.
•A novel multi-model probability battery SOC fusion estimation approach was proposed.•The linear matrix inequality-based H∞ technique is employed to estimate the SOC.•The Bayes theorem has been ...employed to realize the optimal weight for the fusion.•The robustness of the proposed approach is verified by different batteries.•The results show that the proposed method can promote global estimation accuracy.
Due to the strong nonlinearity and complex time-variant property of batteries, the existing state of charge (SOC) estimation approaches based on a single equivalent circuit model (ECM) cannot provide the accurate SOC for the entire discharging period. This paper aims to present a novel SOC estimation approach based on a multiple ECMs fusion method for improving the practical application performance. In the proposed approach, three battery ECMs, namely the Thevenin model, the double polarization model and the 3rd order RC model, are selected to describe the dynamic voltage of lithium-ion batteries and the genetic algorithm is then used to determine the model parameters. The linear matrix inequality-based H-infinity technique is employed to estimate the SOC from the three models and the Bayes theorem-based probability method is employed to determine the optimal weights for synthesizing the SOCs estimated from the three models. Two types of lithium-ion batteries are used to verify the feasibility and robustness of the proposed approach. The results indicate that the proposed approach can improve the accuracy and reliability of the SOC estimation against uncertain battery materials and inaccurate initial states.
Accurate state of charge estimation is essential to improve operation safety and service life of lithium-ion batteries. This paper proposes a synthetic state of charge estimation method for ...lithium-ion batteries based on long short-term memory network modeling and adaptive H-infinity filter. Firstly, the long short-term memory network is exploited to roughly estimate state of charge with the input of voltage, current, operating temperature and state of health. Then, to mitigate the output fluctuation and improve the estimation robustness of long short-term memory network, the adaptive H-infinity filter is employed to flatten the estimation results and further improve the estimation accuracy. A main advantage of the proposed synthetic method lies in that precise battery modeling and burdensome model parameter identification tasks that are imperative in traditional observers or filters can be omitted, thus improving the application efficiency of the proposed algorithm. The proposed method is verified effective on two types of lithium-ion batteries under dynamic working scenarios including the varying temperature and aged conditions. The experimental results highlight that the estimation error of state of charge can be restricted within 2.1% in wide temperature range and different aging states, manifesting its high-precision estimation capacity and strong robustness.
•Long short-term memory network is employed for state of charge estimation.•The adaptive H-infinity filter is employed to smooth the estimation results.•The synthetic method leads to satisfactory estimation under different conditions.•Influence of battery types, dynamic temperature and aged state is incorporated.
This paper presents a new theoretical framework that, by integrating robust statistics and robust control theory, allows us to develop a robust dynamic state estimator of a cyber-physical system. ...This state estimator combines the generalized maximum-likelihood-type (GM) estimator, the unscented Kalman filter (UKF), and the H-infinity filter into a robust H-infinity UKF filter in the Krein space, which is able to handle large system uncertainties as well as suppress outliers while achieving a good statistical efficiency under Gaussian and non-Gaussian process and observation noises. Specifically, we first use the statistical linearization approach to build a linearlike regression model in the Krein space. Then, we show that the H-infinity UKF is just the Krein space Kalman filter that exhibits a bounded estimation error in presence of system uncertainties while minimizing the least squares criterion; consequently, it suffers from a lack of robustness to outliers and non-Gaussian noise. Because the GM estimator is able to handle outliers, but it may yield large estimation errors in the presence of system uncertainties, we propose to combine it with the H-infinity UKF in a robust H-infinity UKF. We carry out a theoretical analysis to demonstrate the connections that our filter has with the H-infinity UKF and the GM-UKF. The good performance of the new filter is demonstrated via extensive simulation performed on the IEEE 39-bus power system.
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