Abstract
Abstract—Steering system of intelligent vehicle is very difficult to execute precise control in driving due to many known and unknown disturbances. Therefore, design of steering algorithm has to be feasible for uncertain external interference, such as uneven pavement and horizontal wind, with automatic correction function for changes in the location of intelligent cars caused by road tilt and horizontal wind. As traditional PID control is impossible to meet the control requirements, according to mechanism of biological immunity, an immune feedback control method was proposed to approximate nonlinearity of T and B cells by BP network. Joint simulations of serpentine condition were carried out by Carsim and Simulink. The results show that trajectory tracking error, operating load, risk of rollover and slip and control stability of control system are synthetically evaluated. The comprehensive evaluation index of automatic steering algorithm under high speed operation is fairly advantageous. Experimental results also show that the algorithm effectively realizes tracking of intelligent vehicle for marking lines and avoidance of obstacles.
Highlights
Steering performance of smart car reflects its operability
Immune feedback control principle was combined with conventional PID control to be designed as a PID self-tuning immune feedback controller (IFC), which improved control performance of the system
As output of PID controller to be the amount of external substance, IFC controller was as following u(k) = K p {1-hf [Du(k - d )]}= ççæ1+
Summary
Steering performance of smart car reflects its operability. In steering, with each wheel subjected to a force, changes of the lateral angle in uncertainty and load transferred, force of each tire susceptible uncertainty and non-linearity of steering system. Conventional PID control could not achieve the requirement[1,2,3,4,5,6,7,8,9,10,11,12], so the author designed IFC(Immune Feedback Control), in which construction of antibody suppression regulatory function was one of the difficulties. In literature[13,14], f (×) was selected as a radial symmetric nonlinear function, which required reasonable adjustment of immune parameters d、h、K p and antibody coniJOE ‒ Vol 15, No 9, 2019. Centration coefficient a .In literature [15,16,17], a two-dimensional fuzzy controller was used to approximate the nonlinear function. BP network was utilized to approximate functions of antibody promotion and inhibition regulation of T cell
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