scholarly journals Using Age Structure for a Multi-stage Optimal Control Model with Random Switching Time

2019 ◽  
Vol 184 (3) ◽  
pp. 1065-1082 ◽  
Author(s):  
Stefan Wrzaczek ◽  
Michael Kuhn ◽  
Ivan Frankovic
Keyword(s):  
Optimal Control ◽  
Switching Time ◽  
Control Model ◽  
Multi Stage ◽  
Numerical Solution Methods ◽  
Solution Methods ◽  
Random Switching ◽  
Age Structured ◽  
Two Stages ◽  
And Control

AbstractThe paper presents a transformation of a multi-stage optimal control model with random switching time to an age-structured optimal control model. Following the mathematical transformation, the advantages of the present approach, as compared to a standard backward approach, are discussed. They relate in particular to a compact and unified representation of the two stages of the model: the applicability of well-known numerical solution methods and the illustration of state and control dynamics. The paper closes with a simple example on a macroeconomic shock, illustrating the workings and advantages of the approach.

scholarly journals Digital twin of mechatronic drive based on the optimal control model of BLDC motor

2020 ◽  
Vol 329 ◽  
pp. 03071
Author(s):  
Sergei Trefilov
Keyword(s):  
Optimal Control ◽  
Viscous Friction ◽  
Control Model ◽  
Control Device ◽  
Operating Conditions ◽  
Bldc Motor ◽  
Digital Twin ◽  
Brushless Dc ◽  
External Forces ◽  
And Control

This paper presents a digital twin of a mechatronic drive based on a brushless DC (BLDC) motor model based on a nonlinear discrete optimal control model. Some parameters of a BLDC motor, such as resistance and inductance of windings, magnetic flux, viscous friction coefficient in bearings, angular velocity and electromagnetic moment, can change due to both degradation of structural elements and external forces. Simulation by a complete enumeration of the values of the parameters of the mechatronic device with a certain step will make it possible to adapt the program of the control device to changing operating conditions according to the criterion of minimizing the control energy by changing the parameters of the state matrices and control of the digital twin. As a result, the accuracy of the movement of the mechatronic device along the given trajectory will increase due to the greater correspondence of the control parameters to the real object.

Integrating Multi-Vehicle Routing and Control: A Comparison of Three Solution Strategies

2018 ◽  
Author(s):  
Tianchen Liu ◽  
Shapour Azarm ◽  
Nikhil Chopra
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Vehicle Routing ◽  
Continuous Time ◽  
Control Model ◽  
Routing Problem ◽  
Solution Strategies ◽  
Shortest Route ◽  
Time Optimal ◽  
And Control

This paper presents the results of a comparison study of three solution strategies for integrating a routing and a control model for a fleet of vehicles planned to visit a number of customer locations. The three strategies considered are: (i) shortest route followed by a constant speed model, (ii) shortest route followed by an optimal control model, and (iii) optimal control-based route. The objective is to compare and contrast optimized costs, a combination of vehicles’ travel time and control cost (or energy consumption), following these different strategies. The routing problem considers a capacitated multi-vehicle routing without time windows but with capacity and customer demand requirements. The control problem considers a continuous-time optimal control problem. Using the data from a benchmark multi-vehicle routing problem, as an example, it is shown that when compared with using a commonly used constant speed model for all vehicles, the optimized cost can be reduced by incorporating optimal control strategies. To the best of our knowledge, this is the first study in the literature that compares solution strategies for control-based vehicle routing, and in particular, formulates and explores continuous time optimal control combined with capacitated multi-vehicle routing. Furthermore, the effect of existence of wind on the vehicle dynamic equations is considered, and optimal results of the routing problem with different wind directions are compared.

A Multi-Stage Optimization Formulation for MPC-Based Obstacle Avoidance in Autonomous Vehicles Using a LIDAR Sensor

2014 ◽  
Author(s):  
Jiechao Liu ◽  
Paramsothy Jayakumar ◽  
Jeffrey L. Stein ◽  
Tulga Ersal
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Obstacle Avoidance ◽  
High Speed ◽  
Optimal Solution ◽  
Multi Stage ◽  
Lift Off ◽  
And Control ◽  
Control Delays

The dynamics of an autonomous unmanned ground vehicle (UGV) that is at least the size of a passenger vehicle are critical to consider during obstacle avoidance maneuvers to ensure vehicle safety. Methods developed so far do not take vehicle dynamics and sensor limitations into account simultaneously and systematically to guarantee the vehicle’s dynamical safety during avoidance maneuvers. To address this gap, this paper presents a model predictive control (MPC) based obstacle avoidance algorithm for high-speed, large-size UGVs that perceives the environment only through the information provided by a sensor, takes into account the sensing and control delays and the dynamic limitations of the vehicle, and provides smooth and continuous optimal solutions in terms of minimizing travel time. Specifically, information about the environment is obtained using an on-board Light Detection and Ranging (LIDAR) sensor. Ensuring the vehicle’s dynamical safety is translated into avoiding single tire lift-off. The obstacle avoidance problem is formulated as a multi-stage optimal control problem with a unique optimal solution. To solve the optimal control problem, it is transcribed into a nonlinear programming (NLP) problem using a pseudo-spectral method, and solved using the interior-point method. Sensing and control delays are explicitly taken into consideration in the formulation. Simulation results show that the algorithm is capable of generating smooth control commands to avoid obstacles while guaranteeing dynamical safety.

Interference mitigation in point to point wireless sensor networks using LSP protocol and time division multiplexing approach

2020 ◽  
Vol 39 (4) ◽  
pp. 5449-5458
Author(s):  
A. Arokiaraj Jovith ◽  
S.V. Kasmir Raja ◽  
A. Razia Sulthana
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Control Parameter ◽  
Interference Mitigation ◽  
Wireless Sensor ◽  
Point To Point ◽  
A Minor ◽  
Two Stages ◽  
Time Division ◽  
And Control

Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.

An LQ Approach to Active Control of Vibrations in Helicopters

1996 ◽  
Vol 118 (3) ◽  
pp. 482-488 ◽  
Author(s):  
Sergio Bittanti ◽  
Fabrizio Lorito ◽  
Silvia Strada
Keyword(s):  
Optimal Control ◽  
Active Control ◽  
Linear Quadratic ◽  
Control Effort ◽  
Vibration Effect ◽  
Suitable Definition ◽  
Lq Optimal Control ◽  
The One ◽  
Definition Of ◽  
And Control

In this paper, Linear Quadratic (LQ) optimal control concepts are applied for the active control of vibrations in helicopters. The study is based on an identified dynamic model of the rotor. The vibration effect is captured by suitably augmenting the state vector of the rotor model. Then, Kalman filtering concepts can be used to obtain a real-time estimate of the vibration, which is then fed back to form a suitable compensation signal. This design rationale is derived here starting from a rigorous problem position in an optimal control context. Among other things, this calls for a suitable definition of the performance index, of nonstandard type. The application of these ideas to a test helicopter, by means of computer simulations, shows good performances both in terms of disturbance rejection effectiveness and control effort limitation. The performance of the obtained controller is compared with the one achievable by the so called Higher Harmonic Control (HHC) approach, well known within the helicopter community.

scholarly journals Protection and Response of a Tertiary Hospital in Shenzhen, China to the COVID-19 Outbreak—the Practice of the Comprehensive Response Mode

2021 ◽  
pp. 1-17
Author(s):  
Benling Hu ◽  
Le Yang ◽  
Chan Wei ◽  
Min Luo
Keyword(s):  
Prevention And Control ◽  
Tertiary Hospital ◽  
Control Model ◽  
Normal Operation ◽  
Process Reengineering ◽  
Equipment Management ◽  
Hospital Acquired Infection ◽  
Public Health Emergencies ◽  
Hospital Acquired ◽  
And Control

ABSTRACT Objective: To evaluate the management mode for the prevention and control of coronavirus 2019 (COVID-19) transmission utilized at a general hospital in Shenzhen, China, with the aim to maintain the normal operation of the hospital. Methods: From January 2, 2020 to April 23, 2020, Hong Kong–Shenzhen Hospital, a tertiary hospital in Shenzhen, has operated a special response protocol named comprehensive pandemic prevention and control model, which mainly includes six aspects: 1) human resource management; 2) equipment management; 3) logistics management; 4) cleaning, disinfection and process reengineering; 5) environment layout; 6) and training and assessment. The detail of every aspect was described and its efficiency was evaluated. Results: A total of 198,802 patients were received. Of those, 10,821 were hospitalized; 26,767 were received by the emergency department and fever clinics; 288 patients were admitted for observation with fever; and 324 were admitted as suspected cases for isolation. Under the protocol of comprehensive pandemic prevention and control model, no case of hospital-acquired infection with COVID-19 occurred among the inpatients or staff. Conclusion: The present comprehensive response model may be useful in large public health emergencies to ensure appropriate management and protect the health and life of individuals.

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