scholarly journals Vehicle Sliding Mode Control with Adaptive Upper Bounds: Static versus Dynamic Allocation to Saturated Tire Forces

2012 ◽  
Vol 2012 ◽  
pp. 1-31 ◽  
Author(s):  
Ali Tavasoli ◽  
Mahyar Naraghi

Nonlinear vehicle control allocation is achieved through distributing the task of vehicle control among individual tire forces, which are constrained to nonlinear saturation conditions. A high-level sliding mode control with adaptive upper bounds is considered to assess the body yaw moment and lateral force for the vehicle motion. The proposed controller only requires the online adaptation of control gains without acquiring the knowledge of upper bounds on system uncertainties. Static and dynamic control allocation approaches have been formulated to distribute high-level control objectives among the system inputs. For static control allocation, the interior-point method is applied to solve the formulated nonlinear optimization problem. Based on the dynamic control allocation method, a dynamic update law is derived to allocate vehicle control to tire forces. The allocated tire forces are fed into a low-level control module, where the applied torque and active steering angle at each wheel are determined through a slip-ratio controller and an inverse tire model. Computer simulations are used to prove the significant effects of the proposed control allocation methods on improving the stability and handling performance. The advantages and limitations of each method have been discussed, and conclusions have been derived.

2009 ◽  
Vol 42 (8) ◽  
pp. 265-270 ◽  
Author(s):  
H. Alwi ◽  
C. Edwards ◽  
O. Stroosma ◽  
J.A. Mulder

2017 ◽  
Vol 13 (3) ◽  
pp. 55-63
Author(s):  
Bashar Fateh Midhat ◽  
Amjad Jaleel Humaidi

Abstract In this work, diabetic glucose concentration level control under disturbing meal has been controlled using two set of advanced controllers. The first set is sliding mode controllers (classical and integral) and the second set is represented by optimal LQR controllers (classical and Min-, ax). Due to their characteristic features of disturbance rejection, both integral sliding mode controller and LQR Minmax controller are dedicated here for comparison. The Bergman minimal mathematical model was used to represent the dynamic behavior of a diabetic patient’s blood glucose concentration to the insulin injection. Simulations based on Matlab/Simulink, were performed to verify the performance of each controller. In spite that Min-max optimal controller gave better disturbance rejection capability than classical optimal controller, classical sliding mode controller could outperform Min-max controller. However, it has been shown that integral sliding mode controller is the best of all in terms of disturbance rejection capability.   Key words: Optimal LQR control, Optimalminimax control, Sliding mode control, Integral sliding mode control.


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