Generalized explicit guidance with optimal time-to-go and realistic final velocity

2019 ◽  
Vol 233 (13) ◽  
pp. 4926-4942
Author(s):  
Sabyasachi Mondal ◽  
Radhakant Padhi
Keyword(s):  
Optimal Solution ◽  
Optimal Time ◽  
Optimal Solutions ◽  
Final Velocity ◽  
Velocity Magnitude ◽  
Guidance Law ◽  
Optimal Guidance ◽  
Input Parameters ◽  
The Cost

This paper presents an approach to compute the optimal time-to-go and final velocity magnitude in the Generalized Explicit (GENEX) guidance. Time-to-go and final velocity magnitude are two critical input parameters in GENEX guidance implementation. Optimal time-to-go selects that optimal solution which yields less cost compared to the costs yielded by other optimal solutions. In addition to it, the input of realistic final velocity lowers the cost further. These developments relax the existing limitations of GENEX, thereby making this optimal guidance law more optimal, effective and generic.

scholarly journals Stability of Solutions for Parametric Inverse Nonlinear Cost Transportation Problem

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2027
Author(s):  
Abd Allah A. Mousa ◽  
Yousria Abo-Elnaga
Keyword(s):  
Nonlinear Programming ◽  
Transportation Problem ◽  
Feasible Solution ◽  
Optimal Solution ◽  
Solution Stability ◽  
Tuning Parameters ◽  
Input Parameters ◽  
Feasible Alternative ◽  
The Stability ◽  
The Cost

This paper investigates the solution for an inverse of a parametric nonlinear transportation problem, in which, for a certain values of the parameters, the cost of the unit transportation in the basic problem are adapted as little as possible so that the specific feasible alternative become an optimal solution. In addition, a solution stability set of these parameters was investigated to keep the new optimal solution (feasible one) is unchanged. The idea of this study based on using a tuning parameters λ∈Rm in the function of the objective and input parameters υ∈Rl in the set of constraint. The inverse parametric nonlinear cost transportation problem P(λ,υ), where the tuning parameters λ∈Rm in the objective function are tuned (adapted) as less as possible so that the specific feasible solution x∘ has been became the optimal ones for a certain values of υ∈Rl, then, a solution stability set of the parameters was investigated to keep the new optimal solution x∘ unchanged. The proposed method consists of three phases. Firstly, based on the optimality conditions, the parameter λ∈Rm are tuned as less as possible so that the initial feasible solution x∘ has been became new optimal solution. Secondly, using input parameters υ∈Rl resulting problem is reformulated in parametric form P(υ). Finally, based on the stability notions, the availability domain of the input parameters was detected to keep its optimal solution unchanged. Finally, to clarify the effectiveness of the proposed algorithm not only for the inverse transportation problems but also, for the nonlinear programming problems; numerical examples treating the inverse nonlinear programming problem and the inverse transportation problem of minimizing the nonlinear cost functions are presented.

Time-energy optimal guidance strategy for realistic interceptor using pseudospectral method

2020 ◽  
Vol 42 (13) ◽  
pp. 2361-2371 ◽  
Author(s):  
Arunava Banerjee ◽  
Mashuq Nabi ◽  
T. Raghunathan
Keyword(s):  
Optimal Control ◽  
Pseudospectral Method ◽  
Two Dimensional ◽  
Energy Usage ◽  
Proportional Navigation ◽  
Guidance Law ◽  
Optimal Guidance ◽  
Legendre Pseudospectral Method ◽  
The Cost ◽  
Guidance Laws

This paper proposes the use of Legendre pseudospectral method (PSM) to obtain the optimal guidance strategy for a two-dimensional interceptor problem. An optimal control problem is formulated that addresses the conflicting objective of minimizing the energy usage, along with minimizing the time taken by missile to capture the target. The PSM-based guidance strategy is compared with other conventional guidance laws such as pure proportional navigation (PPN) guidance law and also evolutionary algorithm inspired differential evolution tuned proportional navigation (DEPN) guidance law. A scheme by which the PSM guidance strategy can be applied online is also included in this paper. The cost function value and the interception time indicates the superiority of the PSM-based guidance strategy.

scholarly journals A New Optimal Guidance Law with Impact Time and Angle Constraints Based on Sequential Convex Programming

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Pei Pei ◽  
Jiang Wang
Keyword(s):  
Convex Programming ◽  
Optimization Problem ◽  
Impact Angle ◽  
Lateral Acceleration ◽  
Optimal Time ◽  
Proportional Navigation ◽  
Impact Time ◽  
Guidance Law ◽  
Sequential Convex Programming ◽  
Optimal Guidance

This paper proposed an optimal time-varying proportional navigation guidance law based on sequential convex programming. The guidance law can achieve the desired impact angle and impact time with look angle and lateral acceleration constraints. By treating the multiconstraints’ guidance problem as an optimization problem and changing the independent variable to linearize the problem and constraints, the original nonlinear and nonconvex problem is transformed into a series of convex optimization problem so that it can be quickly solved by sequential convex programming. Numerical simulations compared to nonlinear programming and traditional analytical guidance law demonstrate the effectiveness and efficiency of the proposed algorithm. Finally, the proposed guidance law is verified to satisfy different impact time periods and impact angle constraints.

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

scholarly journals Inclusion of Hydraulic Controls in Rehabilitation Models of Drainage Networks to Control Floods

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 514
Author(s):  
Leonardo Bayas-Jiménez ◽  
F. Javier Martínez-Solano ◽  
Pedro L. Iglesias-Rey ◽  
Daniel Mora-Melia ◽  
Vicente S. Fuertes-Miquel
Keyword(s):  
Genetic Algorithm ◽  
Drainage System ◽  
Optimal Solution ◽  
Hydraulic Control ◽  
Drainage Systems ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Extreme Rain ◽  
Rain Events ◽  
The Cost

A problem for drainage systems managers is the increase in extreme rain events that are increasing in various parts of the world. Their occurrence produces hydraulic overload in the drainage system and consequently floods. Adapting the existing infrastructure to be able to receive extreme rains without generating consequences for cities’ inhabitants has become a necessity. This research shows a new way to improve drainage systems with minimal investment costs, using for this purpose a novel methodology that considers the inclusion of hydraulic control elements in the network, the installation of storm tanks and the replacement of pipes. The presented methodology uses the Storm Water Management Model for the hydraulic analysis of the network and a modified Genetic Algorithm to optimize the network. In this algorithm, called the Pseudo-Genetic Algorithm, the coding of the chromosomes is integral and has been used in previous studies of hydraulic optimization. This work evaluates the cost of the required infrastructure and the damage caused by floods to find the optimal solution. The main conclusion of this study is that the inclusion of hydraulic controls can reduce the cost of network rehabilitation and decrease flood levels.

scholarly journals Optimal Renovation Strategies through Life-Cycle Analysis in a Pilot Building Located in a Mild Mediterranean Climate

2021 ◽  
Vol 11 (4) ◽  
pp. 1423
Author(s):  
José Manuel Salmerón Lissen ◽  
Cristina Isabel Jareño Escudero ◽  
Francisco José Sánchez de la Flor ◽  
Miriam Navarro Escudero ◽  
Theoni Karlessi ◽  
...  
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Mediterranean Climate ◽  
Building Envelope ◽  
Economic Life ◽  
Hot Water ◽  
Optimal Solutions ◽  
Building Stock ◽  
Existing Building ◽  
The Cost

The 2030 climate and energy framework includes EU-wide targets and policy objectives for the period 2021–2030 of (1) at least 55% cuts in greenhouse gas emissions (from 1990 levels); (2) at least 32% share for renewable energy; and (3) at least 32.5% improvement in energy efficiency. In this context, the methodology of the cost-optimal level from the life-cycle cost approach has been applied to calculate the cost of renovating the existing building stock in Europe. The aim of this research is to analyze a pilot building using the cost-optimal methodology to determine the renovation measures that lead to the lowest life-cycle cost during the estimated economic life of the building. The case under study is an apartment building located in a mild Mediterranean climate (Castellon, SP). A package of 12 optimal solutions has been obtained to show the importance of the choice of the elements and systems for renovating building envelopes and how energy and economic aspects influence this choice. Simulations have shown that these packages of optimal solutions (different configurations for the building envelope, thermal bridges, airtightness and ventilation, and domestic hot water production systems) can provide savings in the primary energy consumption of up to 60%.

scholarly journals Temporal concatenation for Markov decision processes

2021 ◽  
pp. 1-28
Author(s):  
Ruiyang Song ◽  
Kuang Xu
Keyword(s):  
Markov Decision Processes ◽  
Large Scale ◽  
Optimal Solution ◽  
Upper Bounds ◽  
Black Box ◽  
Decision Processes ◽  
Optimal Solutions ◽  
Wide Range ◽  
Markov Decision ◽  
Speed Up

We propose and analyze a temporal concatenation heuristic for solving large-scale finite-horizon Markov decision processes (MDP), which divides the MDP into smaller sub-problems along the time horizon and generates an overall solution by simply concatenating the optimal solutions from these sub-problems. As a “black box” architecture, temporal concatenation works with a wide range of existing MDP algorithms. Our main results characterize the regret of temporal concatenation compared to the optimal solution. We provide upper bounds for general MDP instances, as well as a family of MDP instances in which the upper bounds are shown to be tight. Together, our results demonstrate temporal concatenation's potential of substantial speed-up at the expense of some performance degradation.

scholarly journals Time-jerk optimal trajectory planning of hydraulic robotic excavator

2021 ◽  
Vol 13 (7) ◽  
pp. 168781402110346
Author(s):  
Yunyue Zhang ◽  
Zhiyi Sun ◽  
Qianlai Sun ◽  
Yin Wang ◽  
Xiaosong Li ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
High Efficiency ◽  
Optimal Solution ◽  
Optimal Time ◽  
Target Point ◽  
Robotic Excavator ◽  
The Impact ◽  
Optimal Trajectory Planning

Due to the fact that intelligent algorithms such as Particle Swarm Optimization (PSO) and Differential Evolution (DE) are susceptible to local optima and the efficiency of solving an optimal solution is low when solving the optimal trajectory, this paper uses the Sequential Quadratic Programming (SQP) algorithm for the optimal trajectory planning of a hydraulic robotic excavator. To achieve high efficiency and stationarity during the operation of the hydraulic robotic excavator, the trade-off between the time and jerk is considered. Cubic splines were used to interpolate in joint space, and the optimal time-jerk trajectory was obtained using the SQP with joint angular velocity, angular acceleration, and jerk as constraints. The optimal angle curves of each joint were obtained, and the optimal time-jerk trajectory planning of the excavator was realized. Experimental results show that the SQP method under the same weight is more efficient in solving the optimal solution and the optimal excavating trajectory is smoother, and each joint can reach the target point with smaller angular velocity, and acceleration change, which avoids the impact of each joint during operation and conserves working time. Finally, the excavator autonomous operation becomes more stable and efficient.

scholarly journals Carbon Emission Reduction of Apparel Material Distribution Based on Multi-Objective Genetic Algorithm (NSGA-II)

2019 ◽  
Vol 11 (9) ◽  
pp. 2571
Author(s):  
Xujing Zhang ◽  
Lichuan Wang ◽  
Yan Chen
Keyword(s):  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Optimal Solution ◽  
Material Distribution ◽  
Low Carbon ◽  
Nsga Ii ◽  
Management Objectives ◽  
Multi Objective Genetic Algorithm ◽  
Distribution Process ◽  
The Cost

Low-carbon production has become one of the top management objectives for every industry. In garment manufacturing, the material distribution process always generates high carbon emissions. In order to reduce carbon emissions and the number of operators to meet enterprises’ requirements to control the cost of production and protect the environment, the paths of material distribution were analyzed to find the optimal solution. In this paper, the model of material distribution to obtain minimum carbon emissions and vehicles (operators) was established to optimize the multi-target management in three different production lines (multi-line, U-shape two-line, and U-shape three-line), while the workstations were organized in three ways: in the order of processes, in the type of machines, and in the components of garment. The NSGA-II algorithm (non-dominated sorting genetic algorithm-II) was applied to obtain the results of this model. The feasibility of the model and algorithm was verified by the practice of men’s shirts manufacture. It could be found that material distribution of multi-line layout produced the least carbon emissions when the machines were arranged in the group of type.

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