Chaos Propagation in Games of Control for Energy-Efficient Wireless Communications

2016 ◽  
Vol 18 (04) ◽  
pp. 1650012
Author(s):  
Hana Baili
Keyword(s):  
Optimal Control ◽  
Energy Efficient ◽  
Optimization Problem ◽  
Particle System ◽  
Base Station ◽  
Open Loop ◽  
Time Varying ◽  
Multi Objective Optimization ◽  
Martingale Approach ◽  
Stochastic Particle System

The question of energy management is a major engineering challenge in any wireless communication system that is constrained by finite battery resources. In this paper, we address the problem of transmit power control in a multi-user wireless network with a single base station and random time-varying channels transmitting in parallel and interfering between each other. We suggest a stochastic particle system for studying the game of control; specifically, the channels are modeled as purely discontinuous Markov processes with known characteristics. The signal to interference plus noise ratio (SINR) determines the interactions among particles. Dimensionality reduction of the multi-objective optimization problem relies on chaos propagation, i.e., on the fact that the independence of particles persists in time as and when their number becomes large. And then we solve the optimal control problem for one representative of the particle system. Furthermore, we develop a martingale approach for an alternative open-loop optimal control instead of the feedback one since the latter is not computationally feasible.

Optimal Control of Gun Recoil Using Magnetorheological Dampers

2012 ◽  
Author(s):  
Harinder J. Singh ◽  
Norman M. Wereley
Keyword(s):  
Optimal Control ◽  
Mechanical Model ◽  
Optimization Problem ◽  
Mr Damper ◽  
Constant Load ◽  
Multi Objective Optimization ◽  
Bingham Plastic ◽  
Pressure Drops ◽  
Optimization Methodology ◽  
Gun Firing

Optimal control of a gun recoil absorber is investigated for minimizing recoil loads and maximizing rate of fire. A multi-objective optimization problem was formulated by considering the mechanical model of the recoil absorber employing a spring and a magnetorheological (MR) damper. The damper forces are predicted by evaluating pressure drops using Bingham-plastic model. The optimization methodology provides multiple optimal design configurations with a trade-off between recoil load minimization and increased rate of fire. The configurations with minimum recoil load transmissions have lower rate of fire and vice versa. The gun recoil absorber performance is also analyzed for fluctuations in the firing forces. The adaptive control of the MR damper for varying gun firing forces provides a smooth operation by returning the recoil mass to its battery (ready to reload and fire) position without incurring an end-stop impact. Furthermore, constant load transmissions are observed with respect to the recoil stroke by implementing optimal control during the simulated firing events.

STOCHASTIC MODEL PREDICTIVE CONTROL AND PORTFOLIO OPTIMIZATION

2007 ◽  
Vol 10 (02) ◽  
pp. 203-233 ◽  
Author(s):  
FLORIAN HERZOG ◽  
GABRIEL DONDI ◽  
HANS P. GEERING
Keyword(s):  
Optimal Control ◽  
Portfolio Optimization ◽  
Predictive Control ◽  
Asset Allocation ◽  
Optimization Problem ◽  
Open Loop ◽  
Dynamic Portfolio ◽  
Portfolio Optimization Problem ◽  
Dynamic Portfolio Optimization

This paper proposes a solution method for the discrete-time long-term dynamic portfolio optimization problem with state and asset allocation constraints. We use the ideas of Model Predictive Control (MPC) to solve the constrained stochastic control problem. MPC is a solution technique which was developed to solve constrained optimal control problems for deterministic control applications. MPC solves the optimal control problem with a receding horizon where a series of consecutive open-loop optimal control problems is solved. The aim of this paper is to develop an MPC approach to the problem of long-term portfolio optimization when the expected returns of the risky assets are modeled using a factor model based on stochastic Gaussian processes. We prove that MPC is a suboptimal control strategy for stochastic systems which uses the new information advantageously and thus is better than the pure optimal open-loop control. For the open-loop optimal control optimization, we derive the conditional portfolio distribution and the corresponding conditional portfolio mean and variance. The mean and the variance depend on future decision about the asset allocation. For the dynamic portfolio optimization problem, we consider constraints on the asset allocation as well as probabilistic constraints on the attainable values of the portfolio wealth. We discuss two different objectives, a classical mean–variance objective and the objective to maximize the probability of exceeding a predetermined value of the portfolio. The dynamic portfolio optimization problem is stated, and the solution via MPC is explained in detail. The results are then illustrated in a case study.

On closed-loop equilibrium strategies for mean-field stochastic linear quadratic problems

2020 ◽  
Vol 26 ◽  
pp. 41
Author(s):  
Tianxiao Wang
Keyword(s):  
Optimal Control ◽  
Closed Loop ◽  
Optimal Control Problems ◽  
Mean Field ◽  
Open Loop ◽  
Time Inconsistency ◽  
Control Problems ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Equilibrium Strategies

This article is concerned with linear quadratic optimal control problems of mean-field stochastic differential equations (MF-SDE) with deterministic coefficients. To treat the time inconsistency of the optimal control problems, linear closed-loop equilibrium strategies are introduced and characterized by variational approach. Our developed methodology drops the delicate convergence procedures in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. When the MF-SDE reduces to SDE, our Riccati system coincides with the analogue in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. However, these two systems are in general different from each other due to the conditional mean-field terms in the MF-SDE. Eventually, the comparisons with pre-committed optimal strategies, open-loop equilibrium strategies are given in details.

A Survey on Hierarchical Cluster Based Secure Routing Protocols and Key Management Schemes in Wireless Sensor Networks

2018 ◽  
pp. 18-26
Author(s):  
Yugashree Bhadane ◽  
Pooja Kadam
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Key Management ◽  
Energy Efficient ◽  
Base Station ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Management Schemes ◽  
Cluster Based Routing

Now days, wireless technology is one of the center of attention for users and researchers. Wireless network is a network having large number of sensor nodes and hence called as “Wireless Sensor Network (WSN)”. WSN monitors and senses the environment of targeted area. The sensor nodes in WSN transmit data to the base station depending on the application. These sensor nodes communicate with each other and routing is selected on the basis of routing protocols which are application specific. Based on network structure, routing protocols in WSN can be divided into two categories: flat routing, hierarchical or cluster based routing, location based routing. Out of these, hierarchical or cluster based routing is becoming an active branch of routing technology in WSN. To allow base station to receive unaltered or original data, routing protocol should be energy-efficient and secure. To fulfill this, Hierarchical or Cluster base routing protocol for WSN is the most energy-efficient among other routing protocols. Hence, in this paper, we present a survey on different hierarchical clustered routing techniques for WSN. We also present the key management schemes to provide security in WSN. Further we study and compare secure hierarchical routing protocols based on various criteria.

A Split Network based Routing Approach in Wireless Sensor Network to Enhance Network Stability

2019 ◽  
Vol 9 (4) ◽  
pp. 480-487 ◽  
Author(s):  
Hardeep S. Saini ◽  
Dinesh Arora
Keyword(s):  
Energy Consumption ◽  
Sensor Network ◽  
Energy Efficient ◽  
Cluster Head ◽  
Base Station ◽  
Operating Efficiency ◽  
Network Stability ◽  
Major Factors ◽  
Ch Selection

Background & Objective: The operating efficiency of a sensor network totally relies upon the energy that is consumed by the nodes to perform various tasks like data transmission etc. Thus, it becomes mandatory to consume the energy in an intelligent way so that the network can run for a long period. This paper proposed an energy efficient Cluster Head (CH) selection mechanism by considering the distance to Base Station (BS), distance to node and energy as major factors. The concept of volunteer node is also introduced with an objective to reduce the energy consumption of the CH to transmit data from source to BS. The role of the volunteer node is to transmit the data successfully from source to destination or BS. Conclusion: The results are observed with respect to the Alive nodes, dead nodes and energy consumption of the network. The outcome of the proposed work proves that it outperforms the traditional mechanisms.

Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC) for Wireless Sensor Networks

2020 ◽  
Vol 13 (2) ◽  
pp. 168-172
Author(s):  
Ravi Kumar Poluru ◽  
M. Praveen Kumar Reddy ◽  
Syed Muzamil Basha ◽  
Rizwan Patan ◽  
Suresh Kallam
Keyword(s):  
Network Lifetime ◽  
Routing Protocols ◽  
Energy Efficient ◽  
High Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distributed Energy ◽  
Stability Period ◽  
Energy Efficient Clustering

Background:Recently Wireless Sensor Network (WSN) is a composed of a full number of arbitrarily dispensed energy-constrained sensor nodes. The sensor nodes help in sensing the data and then it will transmit it to sink. The Base station will produce a significant amount of energy while accessing the sensing data and transmitting data. High energy is required to move towards base station when sensing and transmitting data. WSN possesses significant challenges like saving energy and extending network lifetime. In WSN the most research goals in routing protocols such as robustness, energy efficiency, high reliability, network lifetime, fault tolerance, deployment of nodes and latency. Most of the routing protocols are based upon clustering has been proposed using heterogeneity. For optimizing energy consumption in WSN, a vital technique referred to as clustering.Methods:To improve the lifetime of network and stability we have proposed an Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC).Results:In simulation results describes the protocol performs better regarding network lifetime and packet delivery capacity compared to EEDEC and DEEC algorithm. Stability period and network lifetime are improved in EADEEC compare to DEEC and EDEEC.Conclusion:The EADEEC is overall Lifetime of a cluster is improved to perform the network operation: Data transfer, Node Lifetime and stability period of the cluster. EADEEC protocol evidently tells that it improved the throughput, extended the lifetime of network, longevity, and stability compared with DEEC and EDEEC.

scholarly journals Braille Block Detection via Multi-Objective Optimization from an Egocentric Viewpoint

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2775
Author(s):  
Tsubasa Takano ◽  
Takumi Nakane ◽  
Takuya Akashi ◽  
Chao Zhang
Keyword(s):  
Optimization Problem ◽  
Line Pair ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Framework ◽  
Visually Impaired People ◽  
Comprehensive Comparison ◽  
Basic Characteristics ◽  
Support Devices

In this paper, we propose a method to detect Braille blocks from an egocentric viewpoint, which is a key part of many walking support devices for visually impaired people. Our main contribution is to cast this task as a multi-objective optimization problem and exploits both the geometric and the appearance features for detection. Specifically, two objective functions were designed under an evolutionary optimization framework with a line pair modeled as an individual (i.e., solution). Both of the objectives follow the basic characteristics of the Braille blocks, which aim to clarify the boundaries and estimate the likelihood of the Braille block surface. Our proposed method was assessed by an originally collected and annotated dataset under real scenarios. Both quantitative and qualitative experimental results show that the proposed method can detect Braille blocks under various environments. We also provide a comprehensive comparison of the detection performance with respect to different multi-objective optimization algorithms.

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