scholarly journals Sub-Optimal Control of Autonomous Wheel Loader With Approximate Dynamic Programming

2019 ◽  
Author(s):  
Tohid Sardarmehni ◽  
Xingyong Song
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Approximate Dynamic Programming ◽  
A Priori ◽  
Optimal Path ◽  
Mean Value ◽  
Wheel Loader ◽  
Engine Model ◽  
Control Objective ◽  
Wheel Loaders

Abstract Optimal control of wheel loaders in short loading cycles is studied in this paper. For modeling the wheel loader, the data from a validated diesel engine model is used to find a control oriented mean value engine model. The driveline is modeled as a switched system with three constant gear ratios (modes) of −60 for backwarding, 60 for forwarding, and zero for stopping. With these three modes, the sequence of active modes in a short loading cycle is fixed as backwarding, stopping, forwarding, and stopping. For the control part, it is assumed that the optimal path is known a priori. Given the mode sequence, the control objective is finding the optimal switching time instants between the modes while the wheel loader tracks the optimal path. To solve the optimal control problem, approximate dynamic programming is used. Simulation results are provided to show the effectiveness of the solution.

scholarly journals Online Adaptive Optimal Control of Vehicle Active Suspension Systems Using Single-Network Approximate Dynamic Programming

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Zhi-Jun Fu ◽  
Bin Li ◽  
Xiao-Bin Ning ◽  
Wei-Dong Xie
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Approximate Dynamic Programming ◽  
Control Method ◽  
Active Suspension ◽  
Suspension System ◽  
Lyapunov Theory ◽  
Adaptive Optimal Control ◽  
Suspension Systems ◽  
Optimal Control Method

In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation) for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP). Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB) equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR) approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass) and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.

Optimal Control of Complex Air-Path Systems for Advanced Diesel Engines

2009 ◽  
Author(s):  
Fengjun Yan ◽  
Benjamin Haber ◽  
Junmin Wang
Keyword(s):  
Optimal Control ◽  
Diesel Engines ◽  
Linear Quadratic Regulator ◽  
Mean Value ◽  
Diffusion Combustion ◽  
Linear Quadratic ◽  
Control Approach ◽  
Engine Model ◽  
Path System ◽  
Linearized Model

This paper describes a linear optimal control approach for advanced diesel engines equipped with complex air-path systems including a dual-loop exhaust gas recirculation (EGR) and a two-stage turbocharger. Such complex air-path systems are instrumental to achieve smooth and stable transient operation of diesel engines running advanced multiple combustion modes such as low temperature diffusion combustion (LTDC) and homogeneous charge compression ignition (HCCI). A mean-value engine model was developed to capture the main dynamics of the advanced air-path system. A linear quadratic regulator (LQR) optimal controller was designed based on a linearized model at a fixed operating point. Simulation results using a high-fidelity detailed GT-Power engine model show the effectiveness of the controller.

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