A stochastic averaging-based optimal control method for nonlinear systems: Application to a building with soil-structure interactions

2016 ◽  
Vol 127 ◽  
pp. 635-644 ◽  
Author(s):  
Omar El-Khoury ◽  
Abdollah Shafieezadeh
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
Soil Structure ◽  
Control Method ◽  
Stochastic Averaging ◽  
Optimal Control Method

scholarly journals Distributed Optimal Control for a Class of Switched Nonlinear Systems with the State Time Delay

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Yuxing Duan ◽  
Baili Su
Keyword(s):  
Optimal Control ◽  
Time Delay ◽  
Nonlinear Systems ◽  
Control Method ◽  
The State ◽  
Switched Nonlinear Systems ◽  
Distributed Optimal Control ◽  
Switching Sequence ◽  
State Time ◽  
Optimal Control Method

This paper is focused on a kind of distributed optimal control design for a class of switched nonlinear systems with the state time delay which have a prescribed switching sequence. Firstly, we design a bounded controller to make the system stable for each mode of the nominal system. Then, a distributed optimal controller which can satisfy input constraint is designed based on the bounded stabilization controller. A sufficient condition to guarantee ultimate boundedness of the system is given based on appropriate assumption. The significance of this paper is that distributed optimal control method is applied to switched nonlinear systems with the state time delay. Finally, a simulation example is given to verify the effectiveness of the proposed method.

An integrated output space partition and optimal control method of multiple-model for nonlinear systems

2018 ◽  
Vol 113 ◽  
pp. 32-43 ◽  
Author(s):  
Chunyue Song ◽  
Bing Wu ◽  
Jun Zhao ◽  
Zuhua Xu
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
Control Method ◽  
Multiple Model ◽  
Space Partition ◽  
Optimal Control Method ◽  
Output Space

scholarly journals A Semi-Continuous PWA Model Based Optimal Control Method for Nonlinear Systems

Processes ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 170
Author(s):  
Xinjian Zhu ◽  
Chunyue Song ◽  
Jun Zhao ◽  
Zuhua Xu
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
Control Method ◽  
Mode Switching ◽  
Multiple Model ◽  
Dynamical Equations ◽  
Piecewise Affine ◽  
Model Based ◽  
Switching Condition ◽  
Optimal Control Method

To alleviate the mode mismatch of multiple model methods for nonlinear systems when completely discrete dynamical equations are adopted, a semi-continuous piecewise affine (SCPWA) model based optimal control method is proposed. Firstly, a SCPWA model is constructed where modes evolve in continuous time and continuous states evolve in discrete time. Thanks to this model, a piecewise affine (PWA) system can switch at any time instant whereas mode switching only occurs at sample instants when a completely discrete PWA model is adopted, which improves the prediction accuracy of multi-models. Secondly, the switching condition is relaxed such that operating subspaces have overlaps and switching condition parameters are introduced. As a consequence, an optimal control problem with fixed mode switching sequence is established. Finally, a SCPWA model based model predictive control (MPC) policy is designed for nonlinear systems. The convergence of the MPC algorithm is proved. Compared with widely used mixed logical dynamic (MLD) model based methods, the proposed method not only alleviates mode mismatch, but also lightens the computing burden, hence improves the control performance and reduces the computation time. Some numerical examples are provided as well to show the efficiency of the method.

The human-like trajectory planning for autonomous vehicles based on optimal control in a test track environment

2021 ◽  
pp. 095440702110090
Author(s):  
Xing Xu ◽  
Minglei Li ◽  
Feng Wang ◽  
Ju Xie ◽  
Xiaohan Wu ◽  
...  
Keyword(s):  
Optimal Control ◽  
Autonomous Vehicles ◽  
Optimal Trajectory ◽  
Control Method ◽  
Autonomous Vehicle ◽  
Trajectory Data ◽  
Test Track ◽  
Optimal Control Method ◽  
The Future ◽  
On The Road

A human-like trajectory could give a safe and comfortable feeling for the occupants in an autonomous vehicle especially in corners. The research of this paper focuses on planning a human-like trajectory along a section road on a test track using optimal control method that could reflect natural driving behaviour considering the sense of natural and comfortable for the passengers, which could improve the acceptability of driverless vehicles in the future. A mass point vehicle dynamic model is modelled in the curvilinear coordinate system, then an optimal trajectory is generated by using an optimal control method. The optimal control problem is formulated and then solved by using the Matlab tool GPOPS-II. Trials are carried out on a test track, and the tested data are collected and processed, then the trajectory data in different corners are obtained. Different TLCs calculations are derived and applied to different track sections. After that, the human driver’s trajectories and the optimal line are compared to see the correlation using TLC methods. The results show that the optimal trajectory shows a similar trend with human’s trajectories to some extent when driving through a corner although it is not so perfectly aligned with the tested trajectories, which could conform with people’s driving intuition and improve the occupants’ comfort when driving in a corner. This could improve the acceptability of AVs in the automotive market in the future. The driver tends to move to the outside of the lane gradually after passing the apex when driving in corners on the road with hard-lines on both sides.

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