The spot market has been gradually recognized as an important alternative purchasing source. To maintain a flexible replenishment strategy, call, put and bidirectional option…
Abstract
Purpose
The spot market has been gradually recognized as an important alternative purchasing source. To maintain a flexible replenishment strategy, call, put and bidirectional option contracts, as a risk hedging, are in combined usage with the spot market, respectively. The purpose of this paper is to analyze a finite-horizon replenishment problem with option contracts in the context of a spot market.
Design/methodology/approach
Based on stochastic dynamic programming, the firm’s optimal replenishment policy with either call, put or bidirectional option contracts is always shown to be order-up-to type, characterized by an upper threshold and a lower one. The corresponding policy parameters in different cases are calculated through an approximate algorithm. This research highlights the effectiveness of option contracts on the firm’s operational strategies and overall profitability.
Findings
This study reveals that the firm is better off with option contracts than without them. When the price parameters are the same for different option contracts, bidirectional option contracts are the best choice among these flexible contracts; otherwise, unilateral option contracts might be either better or worse than bidirectional ones. In addition, if low inventory costs and high spot price volatility are confronted, the firm prefers to call option contracts rather than put ones; otherwise, there exists an opposite conclusion.
Originality/value
In addition to highlight the advantage of option contracts over wholesale price contracts, this paper provides interesting observations with respect to the effect of different option contracts on the firm. Many significant insights derived from this research do not only contribute to the provider’s feasible design of the supply contracts, but also contribute to the user’s rational operational strategies for higher profitability.
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Nana Wan and Xiaozhi Wu
Due to rapid product obsolescence, there is a significant decline in the market prices, which causes that the sale season is often divided into two periods. This paper aims to…
Abstract
Purpose
Due to rapid product obsolescence, there is a significant decline in the market prices, which causes that the sale season is often divided into two periods. This paper aims to consider a class of two-period supply contracts that offer the retailer the ordering flexibility in response to the market changes. This paper analyzes the two-period ordering and coordination problem with option contracts.
Design/methodology/approach
The authors incorporate call, put and bidirectional option contracts into the two-period ordering model. By applying stochastic dynamic programming, the authors derive the retailer’s optimal ordering policies for two periods. By benchmarking the case without option contracts, they highlight the advantage of option contracts. Through the mutual comparisons, the authors also explore the impacts of different option contracts. On this basis, the authors explore the conditions on which two-period supply contracts containing options can coordinate the supply chain.
Findings
This study shows that the retailer is always better off with option contracts. In addition, the effectiveness of different option contracts depends on the option contract parameters. When the parameters are the same for different option contracts, bidirectional option contracts are superior to call and put ones; otherwise, bidirectional option contracts might be superior or inferior to call and put ones. If designed properly, two-period supply contracts containing options can coordinate the two-period supply chain.
Originality/value
This paper is the first to highlight the value of option contracts as well as explore the role of different option contracts on the two-period procurement problem. The insights derived from our analysis can provide a good way on how to help the retailer work more efficiently in a two-period setting.
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Xuanyi Zhou, Jilin He, Dingping Chen, Junsong Li, Chunshan Jiang, Mengyuan Ji and Miaolei He
Nowadays, the global agricultural system is highly dependent on the widespread use of synthetic pesticides to control diseases, weeds and insects. The unmanned aerial vehicle…
Abstract
Purpose
Nowadays, the global agricultural system is highly dependent on the widespread use of synthetic pesticides to control diseases, weeds and insects. The unmanned aerial vehicle (UAV) is deployed as a major part of integrated pest management in a precision agriculture system for accurately and cost-effectively distributing pesticides to resist crop diseases and insect pests.
Design/methodology/approach
With multimodal sensor fusion applying adaptive cubature Kalman filter, the position and velocity are enhanced for the correction and accuracy. A dynamic movement primitive is combined with the Gaussian mixture model to obtain numerous trajectories through the teaching of a demonstration. Further, to enhance the trajectory tracking accuracy under an uncertain environment of the spraying, a novel model reference adaptive sliding mode control approach is proposed for motion control.
Findings
Experimental studies have been carried out to test the ability of the proposed interface for the pesticides in the crop fields. The effectiveness of the proposed interface has been demonstrated by the experimental results.
Originality/value
To solve the path planning problem of a complex unstructured environment, a human-robot skills transfer interface is introduced for the UAV that is instructed to follow a trajectory demonstrated by a human teacher.
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Yanchao Sun, Liangliang Chen and Hongde Qin
This paper aims to investigate the distributed coordinated fuzzy tracking problems for multiple mechanical systems with nonlinear model uncertainties under a directed…
Abstract
Purpose
This paper aims to investigate the distributed coordinated fuzzy tracking problems for multiple mechanical systems with nonlinear model uncertainties under a directed communication topology.
Design/methodology/approach
The dynamic leader case is considered while only a subset of the follower mechanical systems can obtain the leader information. First, this paper approximates the system uncertainties with finite fuzzy rules and proposes a distributed adaptive tracking control scheme. Then, this paper makes a detailed classification of the system uncertainties and uses different fuzzy systems to approximate different kinds of uncertainties. Further, an improved distributed tracking strategy is proposed. Closed-loop systems are investigated using graph theory and Lyapunov theory. Numerical simulations are performed to verify the effectiveness of the proposed methods.
Findings
Based on fuzzy control and adaptive control theories, the desired distributed coordinated tracking control strategies for multiple uncertain mechanical systems are developed.
Originality/value
Compared with most existing literature, the proposed distributed tracking algorithms use fuzzy control and adaptive control techniques to cope with system nonlinear uncertainties of multiple mechanical systems. Moreover, the improved control strategy not only reduces fuzzy rules but also has higher control accuracy.
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Jian Chen, Shaojing Song, Yang Gu and Shanxin Zhang
At present, smartphones are embedded with accelerometers, gyroscopes, magnetometers and WiFi sensors. Most researchers have delved into the use of these sensors for localization…
Abstract
Purpose
At present, smartphones are embedded with accelerometers, gyroscopes, magnetometers and WiFi sensors. Most researchers have delved into the use of these sensors for localization. However, there are still many problems in reducing fingerprint mismatching and fusing these positioning data. The purpose of this paper is to improve positioning accuracy by reducing fingerprint mismatching and designing a weighted fusion algorithm.
Design/methodology/approach
For the problem of magnetic mismatching caused by singularity fingerprint, derivative Euclidean distance uses adjacent fingerprints to eliminate the influence of singularity fingerprint. To improve the positioning accuracy and robustness of the indoor navigation system, a weighted extended Kalman filter uses a weighted factor to fuse multisensor data.
Findings
The scenes of the teaching building, study room and office building are selected to collect data to test the algorithm’s performance. Experiments show that the average positioning accuracies of the teaching building, study room and office building are 1.41 m, 1.17 m, and 1.77 m, respectively.
Originality/value
The algorithm proposed in this paper effectively reduces fingerprint mismatching and improve positioning accuracy by adding a weighted factor. It provides a feasible solution for indoor positioning.
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Taki Eddine Lechekhab, Stojadin Manojlovic, Momir Stankovic, Rafal Madonski and Slobodan Simic
The control of a quadrotor unmanned aerial vehicle (UAV) is a challenging problem because of its highly nonlinear dynamics, under-actuated nature and strong cross-couplings. To…
Abstract
Purpose
The control of a quadrotor unmanned aerial vehicle (UAV) is a challenging problem because of its highly nonlinear dynamics, under-actuated nature and strong cross-couplings. To solve this problem, this paper aims to propose a robust control strategy, based on a concept of active disturbance rejection control (ADRC).
Design/methodology/approach
The altitude/attitude dynamics of a quadrotor is reformulated into the ADRC framework. Three distinct variations of the error-based ADRC algorithms, with different structures of generalized extended state observers (GESO), are derived for the altitude/attitude trajectory-following task. The convergence of the observation part is proved based on the singular perturbation theory. Through a frequency analysis and a quantitative comparison in a simulated environment, each design is shown to have certain advantages and disadvantages in terms of tracking accuracy and robustness. The digital prototypes of the proposed controllers for quadrotor altitude and attitude control channels are designed and validated through real-time hardware-in-the-loop (HIL) co-simulation, with field-programmable gate array (FPGA) hardware.
Findings
The effects of unavailable reference time-derivatives can be estimated by the ESO and rejected through the outer control loop. The higher order ESOs demonstrate better performances, but with reductions of stability margins. Time-domain simulation analysis reveals the benefits of the proposed control structure related to classical control approach. Real-time FPGA-based HIL co-simulations validated the performances of the considered digital controllers in typical quadrotor flight scenarios.
Practical implications
The conducted study forms a set of practical guidelines for end-users for selecting specific ADRC design for quadrotor control depending on the given control objective and work conditions. Furthermore, the paper presents detailed procedure for the design, simulation and validation of the embedded FPGA-based quadrotor control unit.
Originality/value
In light of the currently available literature on error-based ADRC, a comprehensive approach is applied here, which includes the design of error-based ADRC with different GESOs, its frequency-domain and time-domain analyses using different simulation of UAV flight scenarios, as well as its FPGA-based implementation and testing on the real hardware.
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Guoqiang Zhu, He Li, Huan Zhang, Sen Wang and Xiuyu Zhang
The purpose of this study is to propose an adaptive fault-tolerant control approach based on output feedback for a class of quadrotor unmanned aerial vehicles system. In the event…
Abstract
Purpose
The purpose of this study is to propose an adaptive fault-tolerant control approach based on output feedback for a class of quadrotor unmanned aerial vehicles system. In the event of a controlled actuator failure, a stable flying of the aircraft can be achieved by selecting an appropriate sliding mode surface.
Design/methodology/approach
Aiming at the actuator failure of quadrotor aircraft during flight in the controllable range, a dynamic surface sliding mode passive fault-tolerant controller based on output feedback is designed based on the strong robustness of sliding mode method. Due to the unknown nonlinearity dynamics and parameter uncertainties in the system, a nonlinear observer is used to estimate them online.
Findings
The stability of the suggested algorithm is established using appropriate Lyapunov functions, and the performance of the proposed control approach is demonstrated using hardware-in-the-loop simulation.
Originality/value
An error performance function is introduced into the controller to ensure the convergence speed and accuracy of errors are within the predetermined range. By using the norm estimation method, there is only one parameter that needs to be updated in each step of the control process, which considerably minimizes the calculation burden. Finally, the validity of the proposed control scheme is verified on the hardware-in-the-loop simulation, and the results show that the proposed control method has achieved the desired results.
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En-Ze Rui, Guang-Zhi Zeng, Yi-Qing Ni, Zheng-Wei Chen and Shuo Hao
Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural…
Abstract
Purpose
Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural network (PINN), which was proposed to encode physical laws into neural networks, is a less data-demanding approach for flow field reconstruction. However, when the fluid physics is complex, it is tricky to obtain accurate solutions under the PINN framework. This study aims to propose a physics-based data-driven approach for time-averaged flow field reconstruction which can overcome the hurdles of the above methods.
Design/methodology/approach
A multifidelity strategy leveraging PINN and a nonlinear information fusion (NIF) algorithm is proposed. Plentiful low-fidelity data are generated from the predictions of a PINN which is constructed purely using Reynold-averaged Navier–Stokes equations, while sparse high-fidelity data are obtained by field or experimental measurements. The NIF algorithm is performed to elicit a multifidelity model, which blends the nonlinear cross-correlation information between low- and high-fidelity data.
Findings
Two experimental cases are used to verify the capability and efficacy of the proposed strategy through comparison with other widely used strategies. It is revealed that the missing flow information within the whole computational domain can be favorably recovered by the proposed multifidelity strategy with use of sparse measurement/experimental data. The elicited multifidelity model inherits the underlying physics inherent in low-fidelity PINN predictions and rectifies the low-fidelity predictions over the whole computational domain. The proposed strategy is much superior to other contrastive strategies in terms of the accuracy of reconstruction.
Originality/value
In this study, a physics-informed data-driven strategy for time-averaged flow field reconstruction is proposed which extends the applicability of the PINN framework. In addition, embedding physical laws when training the multifidelity model leads to less data demand for model development compared to purely data-driven methods for flow field reconstruction.
Details
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Dongfeng Li, Zhengzhong Wang, Andrea Da Ronch and Gang Chen
This paper aims to develop an efficient evaluation method to more intuitively and effectively investigate the influence of the wing fuel mass variations because of fuel burn on…
Abstract
Purpose
This paper aims to develop an efficient evaluation method to more intuitively and effectively investigate the influence of the wing fuel mass variations because of fuel burn on transonic aeroelasticity.
Design/methodology/approach
The proposed efficient aeroelastic evaluation method is developed by extending the standard computational fluid dynamics (CFD)-based proper orthogonal decomposition (POD)/reduced order model (ROM).
Findings
The results of this paper show that the proposed aeroelastic efficient evaluation method can accurately and efficiently predict the aeroelastic response and flutter boundary when the wing fuel mass vary because of fuel burn. It also shows that the wing fuel mass variations have a significant effect on transonic aeroelasticity; the flutter speed increases as the wing fuel mass decreases. Without rebuilding an expensive, time-consuming CFD-based POD/ROM for each wing fuel mass variation, the computational cost of the proposed method is reduced obviously. It also shows that the computational efficiency improvement grows linearly with the number of model cases.
Practical implications
The paper presents a potentially powerful tool to more intuitively and effectively investigate the influence of the wing fuel mass variation on transonic aeroelasticity, and the results form a theoretical and methodological basis for further research.
Originality/value
The proposed evaluation method makes it a reality to apply the efficient standard CFD-based POD/ROM to investigate the influence of the wing fuel mass variation because of fuel burn on transonic aeroelasticity. The proposed efficient aeroelastic evaluation method, therefore, is ideally suited to deal with the investigation of the influence of wing fuel mass variations on transonic aeroelasticity and may have the potential to reduce the overall cost of aircraft design.