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Method for realizing finite time control on nonlinear active suspension system
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An active suspension and limited time technology, applied in the field of control, can solve the problems of large amount of calculation and affect the practical application of neural network, etc., and achieve the effect of compensating time lag
Active Publication Date: 2021-07-13
GUANGDONG UNIV OF TECH
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[0003] In the existing literature on the nonlinearity of the finite-time stability of the system and the active suspension system, most of them use neural networks or adaptive neural networks to fit the nonlinear functions of the system. The amount of calculation is large, which seriously affects the practical application of neural networks
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Embodiment 1
[0074] see Figure 1-Figure 3 , the present invention realizes the method for finite time control to nonlinear active suspension system, comprises the following steps:
[0075] (1), establish the active suspension system model equation, analyze the spatial state of the active suspension system and the performance index that needs to be improved, wherein,
[0076] Performance indicators to be improved include sprung mass acceleration suspension deflection z s -z u , Tire deflection z u -z r ;
[0077] The described active suspension system model equation is:
[0078]
[0079] Among them, z s ,z u are the vertical displacements of the sprung and unsprung masses, respectively, z r is the input of the road, m s ,m u are the sprung and unsprung masses, respectively, u is the active control force generator with constant time delay τ, f s ,f d is the spring force and damping force function of the suspension components with nonlinear factors, f us ,f ud Spring force...
Embodiment 2
[0128] The following compares a passive suspension system (PSS) without a controller, a finite-time controller (FT) with a control law, and a target controller (GNNFT) with a controller law;
[0129] (1), sinusoidal road test
[0130] The parameter settings of the active suspension model can be found in the table below (Table 1);
[0131]
[0132] Set β=19 / 20,k 1 =1,p 1 =60 / 4,k 2 =100,p 2 = 6, and the executor is assumed to have a constant executor delay;
[0133] The road disturbance is:
[0134] z r =0.002sin(6πt);
[0135] The FT control law is:
[0136] u=m s (u n + u c );
[0137] Among them, u c is the external disturbance compensator, u n is a nominal controller that satisfies:
[0138]
[0139] in,
[0140]
[0141] GNNFT control law u is:
[0142]
[0143] When τ=30ms, it can be clearly seen that the acceleration spectrum of GNNFT (see Figure 4 ) has a peak near the resonance frequency and is a maximum, while FT has another peak in other...
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Abstract
The invention discloses a method for realizing finite time control on a nonlinear active suspensionsystem, which comprises the following steps of: firstly, establishing an active suspensionsystemmodel equation, and analyzing a space state and a performance index needing to be improved of the active suspensionsystem; and then establishing an error system with time delay compensation, and compensating the influence of time delay of the active suspension system through an auxiliary system; secondly, establishing a Lyapunov function relation through an error system, obtaining a virtual control law a1 and a control law u through an inversion technology, and improving corresponding performance indexes; performing training through a grey neural network to obtain an approximate nonlinear function of the compensated error system; and finally, after the control law u is used for correction, generating new smaller time lag influence of the active suspension system,repeatedly and continuously circulating the method within the finite time, therefore stable control over the active suspension system within the finite time is achieved.
Description
technical field [0001] The invention relates to a control method, in particular to a method for realizing limited time control of a nonlinear active suspension system. Background technique [0002] For the control of active suspension systems, most of the existing controls are based on progressive stability. The disadvantage of asymptotic stability is that the time when the system reaches a stable state cannot be determined, and the time to reach a stable state is related to the rapidity of the system, so it is difficult to achieve rapidity of the system based on asymptotic stability control. The control based on finite time stability can make the system reach the stable state within a specified time, so it is more likely to realize the rapidity of the system. [0003] In the existing literature on the nonlinearity of the finite-time stability of the system and the active suspension system, most of them use neural networks or adaptive neural networks to fit the nonlinear fu...
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