scholarly journals On the structure of the set of active sets in constrained linear quadratic regulation

Automatica ◽  
2019 ◽  
Vol 106 ◽  
pp. 61-69 ◽  
Author(s):  
Martin Mönnigmann
Keyword(s):  
Linear Quadratic ◽  
Active Sets ◽  
Linear Quadratic Regulation

scholarly journals Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5538
Author(s):  
Bảo-Huy Nguyễn ◽  
João Pedro F. Trovão ◽  
Ronan German ◽  
Alain Bouscayrol
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Engine Fuel ◽  
Linear Quadratic ◽  
Loop Control ◽  
Parallel Hybrid ◽  
Linear Quadratic Regulation ◽  
Hybrid Electric

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.

scholarly journals Data-driven Linear Quadratic Regulation via Semidefinite Programming

2020 ◽  
Vol 53 (2) ◽  
pp. 3995-4000
Author(s):  
Monica Rotulo ◽  
Claudio De Persis ◽  
Pietro Tesi
Keyword(s):  
Semidefinite Programming ◽  
Data Driven ◽  
Linear Quadratic ◽  
Linear Quadratic Regulation

Dynamic Analysis of Flexible Rotor Suspended by Active Magnetic Bearings With LQR Controller

2018 ◽  
Author(s):  
Yixin Su ◽  
Yanhui Ma ◽  
Qian Shi ◽  
Suyuan Yu
Keyword(s):  
Dynamic Characteristics ◽  
Beam Theory ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Flexible Rotor ◽  
Linear Quadratic ◽  
State Response ◽  
Lagrange’S Equation ◽  
Linear Quadratic Regulation ◽  
Lqr Controller

Dynamic characteristics of active magnetic bearing (AMB)-flexible rotor system are closely related to control law. To analyze dynamic characteristics of flexible rotor suspended by AMBs with linear quadratic regulation (LQR) controller, a simple and effective method based on numerical calculation of unbalanced response is proposed in this article. The model of flexible rotor is established based upon Euler-Bernoulli beam theory and Lagrange’s equation. Disc on the rotor and its Gyro effect are taken into account. LQR controller based on error and its derivative is developed to control electromagnetic force of AMB at each degree of freedom (DOF) in real time. Under the unbalanced exciting force, the steady-state response and transient response in time domain of each node of flexible rotor at 0–4000 rad/s are calculated numerically. The critical speeds of rotor are obtained by identification method quickly and easily.

DEPTH CONTROL OF AN UNDERWATER REMOTELY OPERATED VEHICLE USING NEURAL NETWORK PREDICTIVE CONTROL

2015 ◽  
Vol 74 (9) ◽  
Author(s):  
Mohd Shahrieel Mohd Aras ◽  
Shahrum Shah Abdullah ◽  
Ahmad Fadzli Nizam Abdul Rahman ◽  
Norhaslinda Hasim ◽  
Fadilah Abdul Azis ◽  
...  
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Fuzzy Logic Controller ◽  
Pi Controller ◽  
System Response ◽  
Linear Quadratic ◽  
Remotely Operated Vehicle ◽  
Depth Control ◽  
Linear Quadratic Regulation ◽  
Neural Network Predictive Control

This paper investigates the depth control of an unmanned underwater remotely operated vehicle (ROV) using neural network predictive control (NNPC). The NNPC is applied to control the depth of the ROV to improve the performances of system response in terms of overshoot. To assess the viability of the method, the system was simulated using MATLAB/Simulink by neural network predictive control toolbox. In this paper also investigates the number of data samples (1000, 5000 and 10,000) to train neural network. The simulation reveals that the NNPC has the better performance in terms of its response, but the execution time will be increased. The comparison between other controller such as conventional PI controller, Linear Quadratic Regulation (LQR) and fuzzy logic controller also covered in this paper where the main advantage of NNPC is the fastest system response on depth control. 

scholarly journals Tuning of AC voltage-controlled VSC based Linear Quadratic Regulation

2019 ◽  
Author(s):  
Taoufik Qoria ◽  
Chuanyue Li ◽  
Ko Oue ◽  
Francois Gruson ◽  
Frederic Colas ◽  
...  
Keyword(s):  
Linear Quadratic ◽  
Linear Quadratic Regulation
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