Control variable parameterization and optimization method for stochastic linear quadratic models

2022 ◽  
Vol 154 ◽  
pp. 111638
Author(s):  
Bo Li ◽  
Tian Huang
Keyword(s):  
Control Variable ◽  
Optimization Method ◽  
Linear Quadratic ◽  
Quadratic Models

scholarly journals Robust optimal control of a nonlinear impulsive time-delay system for 1,3-PD fed-batch culture

2021 ◽  
Vol 2113 (1) ◽  
pp. 012022
Author(s):  
Chao Sun
Keyword(s):  
Optimal Control ◽  
Time Delay ◽  
Control Variable ◽  
Optimization Method ◽  
Delay System ◽  
Experimental Result ◽  
Time Delay System ◽  
Robust Optimal Control ◽  
Robust Model ◽  
Feeding Process

Abstract In this paper, taking the feeding process as a form of impulsive and considering the time-delay in fermentation process. A robust model with the time-delay system as the control variable and the time-delay system as the constraint is established. In order to solve this optimal control problem, we have propose an particle swarm optimization method to solve problem. Numerical results show that 1,3-PD yield at the terminal time increases compared with the experimental result.

Design and Instruction Solution of an Optimal Guidance Law for Ship-Air Missile beyond Visual Range

2012 ◽  
Vol 433-440 ◽  
pp. 3831-3836
Author(s):  
Yong Tao Zhao ◽  
Yun An Hu
Keyword(s):  
Control Variable ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Guidance Law ◽  
The Earth ◽  
Optimal Guidance ◽  
Quadratic Optimal Control ◽  
Simulation Results ◽  
Visual Range ◽  
Terminal Guidance

For the case of ship-air missile intercepting the low target beyond visual range by ship-ship coordination, the instruction solution model was presented and an optimal guidance law was designed considering the effect of the curvature of the earth. In the midcourse and terminal guidance segment, the optimal guidance law was designed through applying the concept of the pseudo control variable and the theory of the linear quadratic optimal control. The information of the target was described in the launch coordinates through coordinate transformation to realize the instruction solution for the designed guidance law. The simulation results show that the model of the instruction solution is correct and the designed guidance law is feasible.

A general trajectory optimization method for aircraft taxiing on flight deck of carrier

2018 ◽  
Vol 233 (4) ◽  
pp. 1340-1353 ◽  
Author(s):  
Yu Wu ◽  
Ning Hu ◽  
Xiangju Qu
Keyword(s):  
Optimization Algorithm ◽  
Trajectory Optimization ◽  
Fitness Function ◽  
Control Variable ◽  
Optimization Method ◽  
Operation Efficiency ◽  
Ground Motion Model ◽  
Aircraft System ◽  
Chicken Swarm Optimization ◽  
Flight Deck

Enhancing operation efficiency of flight deck has become a hotspot because it has an important impact on the fighting capacity of the carrier–aircraft system. To improve the operation efficiency, aircraft need taxi to the destination on deck with the optimal trajectory. In this paper, a general method is proposed to solve the trajectory optimization problem for aircraft taxiing on flight deck considering that the existing methods can only deal with the problem in some specific cases. Firstly, the ground motion model of aircraft, the collision detection strategy and the constraints are included in the mathematical model. Then the principles of the chicken swarm optimization algorithm and the generality of the proposed method are explained. In the trajectory optimization algorithm, several strategies, i.e. generation of collocation points, transformation of control variable, and setting of segmented fitness function, are developed to meet the terminal constraints easier and make the search efficient. Three groups of experiments with different environments are conducted. Aircraft with different initial states can reach the targets with the minimum taxiing time, and the taxiing trajectories meet all the constraints. The reason why the general trajectory optimization method is validated in all kinds of situations is also explained.

scholarly journals Maximum Principle for Stochastic Recursive Optimal Control Problems Involving Impulse Controls

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Zhen Wu ◽  
Feng Zhang
Keyword(s):  
Optimal Control ◽  
Maximum Principle ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Optimality Conditions ◽  
Control Variable ◽  
Necessary Optimality Conditions ◽  
Sufficient Optimality Conditions ◽  
Linear Quadratic ◽  
Regular Control

We consider a stochastic recursive optimal control problem in which the control variable has two components: the regular control and the impulse control. The control variable does not enter the diffusion coefficient, and the domain of the regular controls is not necessarily convex. We establish necessary optimality conditions, of the Pontryagin maximum principle type, for this stochastic optimal control problem. Sufficient optimality conditions are also given. The optimal control is obtained for an example of linear quadratic optimization problem to illustrate the applications of the theoretical results.

Factoring spectral matrices in linear-quadratic models

1991 ◽  
Vol 35 (1) ◽  
pp. 39-44 ◽  
Author(s):  
J.A. Ball ◽  
B. Taub
Keyword(s):  
Linear Quadratic ◽  
Quadratic Models

scholarly journals Elevation, pitch and travel axis stabilization of 3DOF helicopter with hybrid control system by GA-LQR based PID controller

2020 ◽  
Vol 10 (2) ◽  
pp. 1868 ◽  
Author(s):  
Ibrahim K. Mohammed ◽  
Abdulla I. Abdulla
Keyword(s):  
Pid Controller ◽  
Hybrid Control ◽  
Research Work ◽  
Linear Quadratic Regulator ◽  
Optimization Method ◽  
Feedback Gain ◽  
Algorithm Optimization ◽  
Linear Quadratic ◽  
Control Approach ◽  
Lqr Controller

This research work presents an efficient hybrid control methodology through combining the traditional proportional-integral-derivative (PID) controller and linear quadratic regulator (LQR) optimal controlher. The proposed hybrid control approach is adopted to design three degree of freedom (3DOF) stabilizing system for helicopter. The gain parameters of the classic PID controller are determined using the elements of the LQR feedback gain matrix. The dynamic behaviour of the LQR based PID controller, is modeled and the formulated in state space form to enable utlizing state feedback controller technique. The performance of the proposed LQR based LQR controller is improved by using Genetic Algorithm optimization method which are adopted to obtain optimum values for LQR controller gain parameters. The LQR-PID hybrid controller is simulated using Matlab environment and its performance is evaluated based on rise time, settling time, overshoot and steady state error parameters to validate the proposed 3DOF helicopter balancing system. Based on GA tuning approach, the simulation results suggest that the hybrid LQR-PID controller can be effectively adopted to stabilize the 3DOF helicopter system.

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