The Use of Integral Adaptation Principle to Synthesize Robust Control of Electric Vehicle Wheel Slip

2019 ◽  
Vol 20 (7) ◽  
pp. 412-416 ◽  
Author(s):  
A. A. Kolesnikov ◽  
A. A. Kuz’menko

The usage of "motor-wheel" systems requires the electric vehicle control system improvement by using the characteristics of the wheel adhesion to the road surface. One of the aspects of such improvement is the enhancement of the algorithms for the functioning of the antilock braking system (ABS). In developing the ABS control algorithms, various approaches and methods of modern control theory are used, including methods based on the estimation of wheel slip, traction force, wheel friction coefficient using linear and nonlinear estimation methods, linear and nonlinear regulators. This work illustrates the application of the principle of high order integral adaptation (PIA) of Synergetic Control Theory (SCT) for constructing a robust control law for an electric vehicle wheel slip. The main features of the SCT contain: firstly, a fundamental change in the goals of the behavior of the synthesized systems; secondly, direct consideration of the natural properties of nonlinear objects; thirdly, the formation of an analytical mechanism for generating feedbacks, i.e. control laws. PIA consists in introducing nonlinear integrators into the control law that compensate for disturbances without their immediate estimation. The obtained in this work control law has a fairly simple structure, is focused on using physically accessible state variables of the braking system, and its implementation does not require immediate estimation of disturbances or building a complex neural network to calculate disturbances. The results of computer simulations of the synthesized robust control law for ABS indicate its effectiveness in functioning under conditions of external environment uncertainty.

2018 ◽  
Vol 19 (11) ◽  
pp. 691-698 ◽  
Author(s):  
G. L. Degtyarev ◽  
R. N. Faizutdinov ◽  
I. O. Spiridonov

In the paper multiobjective robust controller synthesis problem for nonlinear mechanical system described by Lagrange’s equations of the second kind is considered. Such tasks have numerous practical applications, for example in controller design of robotic systems and gyro-stabilized platforms. In practice, we often have to use uncertain mathematical plant models in controller design. Therefore, ensuring robustness in presence of parameters perturbations and unknown external disturbances is an important requirement for designed systems. Much of modern robust control theory is linear. When the actual system exhibits nonlinear behavior, nonlinearities are usually included in the uncertainty set of the plant. A disadvantage of this approach is that resulting controllers may be too conservative especially when nonlinearities are significant. The nonlinear H∞ optimal control theory developed on the basis of differential game theory is a natural extension of the linear robust control theory. Nonlinear theory methods ensure robust stability of designed control systems. However, to determine nonlinear H∞-control law, the partial differential equation have to be solved which is a rather complicated task. In addition, it is difficult to ensure robust performance of controlled processes when using this method. In this paper, methods of linear parameter-varying (LPV) systems are used to synthesize robust control law. It is shown, that Lagrange system may be adequately represented in the form of quasi-LPV model. From the computational point of view, the synthesis procedure is reduced to convex optimization techniques under constraints expressed in the form of linear matrix inequalities (LMIs). Measured parameters are incorporated in the control law, thus ensuring continuous adjustment of the controller parameters to the current plant dynamics and better performance of control processes in comparison with H∞-regulators. Furthermore, the use of the LMIs allows to take into account the transient performance requirements in the controller synthesis. Since the quasi-LPV system depends continuously on the parameter vector, the LMI system is infinite-dimensional. This infinitedimensional system is reduced to a finite set of LMIs by introducing a polytopic LPV representation. The example of multiobjective robust control synthesis for electro-optical device’s line of sight pointing and stabilization system suspended in two-axes inertially stabilized platform is given.


2006 ◽  
Vol 47 (1) ◽  
pp. 34-38 ◽  
Author(s):  
Hiro-o YAMAZAKI ◽  
Masao NAGAI ◽  
Takayoshi KAMADA

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Guodong Yin ◽  
XianJian Jin

A new cooperative braking control strategy (CBCS) is proposed for a parallel hybrid electric vehicle (HEV) with both a regenerative braking system and an antilock braking system (ABS) to achieve improved braking performance and energy regeneration. The braking system of the vehicle is based on a new method of HEV braking torque distribution that makes the antilock braking system work together with the regenerative braking system harmoniously. In the cooperative braking control strategy, a sliding mode controller (SMC) for ABS is designed to maintain the wheel slip within an optimal range by adjusting the hydraulic braking torque continuously; to reduce the chattering in SMC, a boundary-layer method with moderate tuning of a saturation function is also investigated; based on the wheel slip ratio, battery state of charge (SOC), and the motor speed, a fuzzy logic control strategy (FLC) is applied to adjust the regenerative braking torque dynamically. In order to evaluate the performance of the cooperative braking control strategy, the braking system model of a hybrid electric vehicle is built in MATLAB/SIMULINK. It is found from the simulation that the cooperative braking control strategy suggested in this paper provides satisfactory braking performance, passenger comfort, and high regenerative efficiency.


Author(s):  
Yesim Oniz ◽  
Erdal Kayacan ◽  
Okyay Kaynak

The main control objective of an Antilock Braking System (ABS) is to increase the tractive forces between wheel and road surface by keeping the wheel slip at the peak value of μ – λ curve. Conventionally, it is assumed that optimal wheel slip is constant. In this paper, a grey sliding mode controller is proposed to regulate optimal wheel slip depending on the vehicle forward velocity. ABS exhibits strongly nonlinear and uncertain characteristics. To overcome these difficulties, robust control methods should be employed. The concept of grey system theory, which has a certain prediction capability, offers an alternative approach to conventional control methods. The proposed controller anticipates the upcoming values of wheel slip and optimal wheel slip, and takes the necessary action to keep wheel slip at the desired value. The control algorithm is applied to a quarter vehicle model, and it is verified through simulations indicating fast convergence and good performance of the designed controller.


2007 ◽  
Vol 48 (1) ◽  
pp. 22-29 ◽  
Author(s):  
Hiro-o YAMAZAKI ◽  
Yasushi KARINO ◽  
Takayoshi KAMADA ◽  
Masao NAGAI ◽  
Tetsuya KIMURA

2020 ◽  
Vol 1706 ◽  
pp. 012216
Author(s):  
V Dankan Gowda ◽  
M Ramesha ◽  
S B Sridhara ◽  
G Naveena Pai ◽  
Sachin Kumar Patil

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