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As wheeled mobile robots find increasing use in outdoor applications, it becomes more important to reduce energy consumption to perform more missions efficiently with limit energy supply. The purpose of this paper is to survey the current state-of-the-art on energy-efficient motion planning (EEMP) for wheeled mobile robots.

The use of wheeled mobile robots has been increased to replace humans in performing risky missions in outdoor applications, and the requirement of motion planning with efficient energy consumption is necessary. This study analyses a lot of motion planning technologies in terms of energy efficiency for wheeled mobile robots from 2000 to present. The dynamic constraints play a key role in EEMP problem, which derive the power model related to energy consumption. The surveyed approaches differ in the used steering mechanisms for wheeled mobile robots, in assumptions on the structure of the environment and in computational requirements. The comparison among different EEMP methods is proposed in optimal, computation time and completeness.

According to lots of literature in EEMP problem, the research results can be roughly divided into online real-time optimization and offline optimization. The energy consumption is considered during online real-time optimization, which is computationally expensive and time-consuming. The energy consumption model is used to evaluate the candidate motions offline and to obtain the optimal energy consumption motion. Sometimes, this optimization method may cause local minimal problem and even fail to track. Therefore, integrating the energy consumption model into the online motion planning will be the research trend of EEMP problem, and more comprehensive approach to EEMP problem is presented.

EEMP is closely related to robot’s dynamic constraints. This paper mainly surveyed in EEMP problem for differential steered, Ackermann-steered, skid-steered and omni-directional steered robots. Other steering mechanisms of wheeled mobile robots are not discussed in this study.

The survey of performance of various EEMP serves as a reference for robots with different steering mechanisms using in special scenarios.

This paper analyses a lot of motion planning technologies in terms of energy efficiency for wheeled mobile robots from 2000 to present.

In this paper, with the goal of reducing the fuel consumption of UAV, the engine performance optimization is studied and on the basis of aircraft/engine integrated control, the minimum fuel consumption optimization method of engine given thrust is proposed. In the case of keeping the given thrust of the engine unchanged, the main fuel flow of the engine without being connected to the afterburner is optimally controlled so as to minimize the fuel consumption.

In this study, the reference model real-time optimization control method is adopted. The engine reference model uses a nonlinear real-time mathematical model of a certain engine component method. The quasi-Newton method is adopted in the optimization algorithm. According to the optimization variable nozzle area, the turbine drop-pressure ratio corresponding to the optimized nozzle area is calculated, which is superimposed with the difference of the drop-pressure ratio of the conventional control plan and output to the conventional nozzle controller of the engine. The nozzle area is controlled by the conventional nozzle controller.

The engine real-time minimum fuel consumption optimization control method studied in this study can significantly reduce the engine fuel consumption rate under a given thrust. At the work point, this is a low-altitude large Mach work point, which is relatively close to the edge of the flight envelope. Before turning on the optimization controller, the fuel consumption is 0.8124 kg/s. After turning on the optimization controller, you can see that the fuel supply has decreased by about 4%. At this time, the speed of the high-pressure rotor is about 94% and the temperature after the turbine can remain stable all the time.

The optimal control method of minimum fuel consumption for the given thrust of UAV is proposed in this paper and the optimal control is carried out for the nozzle area of the engine. At the same time, a method is proposed to indirectly control the nozzle area by changing the turbine pressure ratio. The relevant UAV and its power plant designers and developers may consider the results of this study to reach a feasible solution to reduce the fuel consumption of UAV.

Fuel consumption optimization can save fuel consumption during aircraft cruising, increase the economy of commercial aircraft and improve the combat radius of military aircraft. With the increasingly wide application of UAVs in military and civilian fields, the demand for energy-saving and emission reduction will promote the UAV industry to improve the awareness of environmental protection and reduce the cost of UAV use and operation.

The authors examine the optimal consumption decisions of households in a micro-founded framework that introduces endogenous default. They study default in the context of a two-period process, assuming three non-overlapping steps of non-payment: delinquency, non-performing loans and bankruptcy (default).

In their model, the authors extend the analysis of loan default to two periods and include agent heterogeneity by considering also saving households. In the optimization problem, the authors obtain first-order conditions for borrowers who do not repay all of their loans (comparing them to those who fully repay them) and also for savers. In addition, by using nonlinear Generalized Method of Moments (GMM), they obtain consistent estimates of the household preference parameters and present the impulse responses of borrowers' consumption to demand shocks.

The authors derive an augmented consumption Euler equation for borrowers, which is a function inter alia of an expected default factor. They estimate this equation and find non-negligible differences in preference parameters relative to values reported in the literature. Further, an ordering by size of the household discount factors is provided empirically. Finally, the impulse responses of borrowers' consumption to a demand shock are found to last more for borrowers who do not fully repay their debts.

This work represents a promising line of research by introducing default in one of the basic components of DSGE models, making the latter more appropriate for analyzing monetary and macro-prudential policies.

The purpose of this paper is to empirically analyze the relationship between risky asset allocation and background risk of Chinese residents.

Using Chinese macroeconomic data, this study uses numerical method to solve dynamic stochastic optimal problem.

When risk of labor income is considered, ratio of risky asset declines with rising of age for those people with same age and wealth state; any of the following situations will lead to lower risky assets holdings: lower labor income growth expectations, higher labor income risk or higher labor and financial market covariance risk.

This study uses real economy investment return as a proxy of risky asset return.

Residents with higher background risks should hold less risky assets, and overcome home‐bias problem during asset allocation.

This study takes two kinds of background risk into consideration: labor income risk, and covariance between labor income and risk asset.

The purpose of this paper is to propose two energy management strategies (EMS) for hybrid electric vehicle, the power system is an hybrid architecture (fuel cell (FC)/battery) with two-converters parallel configuration.

First, the authors present the EMS uses a power frequency splitting to allow a natural frequency decomposition of the power loads and second the EMS uses the optimal control theory, based on the Pontryagin’s minimum principle.

Thanks to the optimal approach, the control objectives will be easily achieved: hydrogen consumption is minimized and FC health is protected.

The simulation results show the effectiveness of the control strategy using optimal control theory in term of improvement of the fuel consumption based on a comparison analysis between the two strategies.

Context is known to affect evaluation for many goods. For example, a house of any given size is more likely to be viewed as adequate the larger it is relative to other houses in the same locale. If evaluations of some goods are more sensitive to context than others, there is no presumption that privately optimal consumption patterns will be socially optimal. Rather, consumers will spend too much on goods whose evaluations depend most strongly on context and too little on those whose evaluations depend least strongly on context. For instance, if evaluations of houses are more sensitive to context than evaluations of leisure, then people will spend too much money on houses and too little time with family and friends. But if context sensitivity is the same for all goods, no distortions result.

This paper suggests theoretical grounds for expecting context sensitivity to differ across goods. Evaluations should be more sensitive to context for goods whose consumption is more readily observed by others and also for goods for which relative consumption is linked to other important payoffs. The quality of school that a child attends, for example, is often strongly linked to its parents’ relative expenditures on housing.

A survey of empirical evidence suggests that observed differences in context sensitivity track the differences predicted on theoretical grounds.

The purpose of this paper is to examine the feasibility and design of zero-energy buildings (ZEBs) in cold and semi-arid climates. In this study, to maximize the use of renewable energy, energy consumption is diminished using passive solar architecture systems and techniques.

The case study is a residential building with a floor area of 100 m² and four inhabitants in the cold and semi-arid climate, northeast of Iran. For thermal simulation, the climate data such as air temperature, sunshine hours, wind, precipitation and hourly sunlight, are provided from the meteorological station and weather databases of the region. DesignBuilder software is applied for simulation and dynamic analysis of the building, as well as PVsyst software to design and evaluate renewable energy performance.

The simulation results show a 30% decrease in annual energy consumption of the building by complying with the principles of passive design (optimal selection of direction, Trombe wall, shade, proper insulation selection) from 25,443 kWh to 17,767 kWh. Then, the solar energy photovoltaic (PV) system is designed using PVsyst software, taking into account the annual energy requirement and the system’s annual energy yield is estimated to be 26,291 kWh.

The adaptive comparison of the values obtained from the energy analysis indicated that constructing a ZEB is feasible in cold and semi-arid conditions and is considered an effective step to achieve sustainable and environmentally friendly construction.