US 12,271,663 B2
Method for collaborative controlling networks resilience of unmanned cluster system, terminal, and storage medium thereof
Xiaomin Zhao, Hefei (CN); Zhengrong Cui, Hefei (CN); Fangfang Dong, Hefei (CN); Chang Pan, Hefei (CN); and Binhe Li, Hefei (CN)
Assigned to HEFEI UNIVERSITY OF TECHNOLOGY, Hefei (CN)
Filed by HEFEI UNIVERSITY OF TECHNOLOGY, Hefei (CN)
Filed on Mar. 13, 2024, as Appl. No. 18/603,317.
Claims priority of application No. 202310282721.5 (CN), filed on Mar. 22, 2023.
Prior Publication US 2024/0330527 A1, Oct. 3, 2024
Int. Cl. G06F 30/18 (2020.01); G05D 1/69 (2024.01)
CPC G06F 30/18 (2020.01) [G05D 1/69 (2024.01)] 13 Claims
OG exemplary drawing
 
1. An unmanned cluster system comprising a plurality of unmanned systems and a computer terminal, wherein the computer terminal comprises a processor and storage storing computer programs to be executed by the processor, and the computer programs are for:
step S1, collecting both targets for tracking and spatial status information of each unmanned system in the unmanned cluster system;
step S2, establishing a kinematic model of the unmanned cluster system in order to get a constraint following error of each unmanned system according to the target and the spatial status information correspondingly;
step S3, constructing a dynamic model of each unmanned system, the dynamic models being affected by an uncertainty of system parameters and an influence of network attack inputs of the unmanned cluster system;
step S4, constructing an uncertainty boundary function of each unmanned system based on the dynamic model correspondingly, and the uncertainty boundary function being relative to the uncertainty and the influence; and
step S5, constructing an adaptive robust controller of each unmanned system according to the constraint following error and the uncertainty boundary function correspondingly;
wherein the step for constructing the uncertainty boundary function comprises:
step S41, decomposing the dynamic model of an i'th unmanned system as follows according to an effect on the uncertainty of system parameters:

OG Complex Work Unit Math
in these formulas, custom characteri being defined as a nominal part and the Δcustom characteri(pi,t) being defined as an uncertain part; custom characteri(pi,custom characteri,t) meaning an inertia matrix of the i'th unmanned system; each of Hi, ΔHi, and Ei being defined as an alegbraic quantity; i meaning a sequence number of the unmanned system on the unmanned cluster system, i∈N+, N+={1, 2, . . . , n}; n meaning a total number of the unmanned systems; pi meaning a spatial position of the i'th unmanned system; t meaning time; custom characteri meaning the uncertainty of system parameters of the i'th unmanned system;
step S42, decomposing an input matrix Dai of the i'th unmanned system based on the network attack input as follows:

OG Complex Work Unit Math
in this formula,

OG Complex Work Unit Math
Ai meaning a constrain matrix; and
step S43, getting a boundary function Θi(γi,pi,pi,t) for describing uncertainty boundary information of the uncertainty and the influence, the step of getting the boundary function Θi(γi,pi,pi,t) comprising:
(a) constructing a formula with a constant vector γi and the boundary function Θi(γi,pi,pi,t) as follows:

OG Complex Work Unit Math
in this formula, γi meaning uncertain variables of the i'th unmanned system, Ki meaning a positive definite matrix of the i'th unmanned system, bi meaning a second-order constrained vector of the i'th unmanned system; νai meaning the network attack input of the i'th unmanned system, νai∈Σi⊂Rl, Σi⊂Rl meaning a compact set of the unmanned cluster system, Rl meaning l dimensional vector space in a field of real numbers, Σi meaning a possible boundary of νai; custom characteri(t) meaning the uncertainty of system parameters of the i'th unmanned system, custom characteri(t)⊂Γi⊂Rp, Rp meaning p dimensional vector space in the field of real numbers, Γi meaning a possible boundary of custom characteri(t); Ci(pi,pi,custom characteri,t)pi meaning a Coriolis/Centrifugal force; Gi(pi,custom characteri,t) meaning a gravitational force; Fi(pi,pi,custom characteri,t) meaning the other force; δEi meaning a constant satisfying the following condition:

OG Complex Work Unit Math
in this formula,

OG Complex Work Unit Math
λmin(⋅) meaning a minimum value of a matrix eigenvalue; and
(b) the boundary function Θi(γi,pi,pi,t) being a continuous concave function as for the constant vector γi, and to any vector in the field of real numbers, γi1 and γi2 meeting the following condition:

OG Complex Work Unit Math
wherein the step of constructing the adaptive robust controller comprises:
step S51, constructing an adaptive law {dot over (γ)}i for estimating the constant vector γi based on the constraint following error ϵi and the boundary function Θi(γi,pi,pi,t),

OG Complex Work Unit Math
in this formula, γi being an estimated value of γi, γi(t0)>0, t0 meaning an initial time; Yi1 and Yi2 both meaning a parameter matrix with adjustable adaptive law, Yi1>0, Yi2>0, pi meaning a speed of the i'th unmanned system;
step S52, constructing an adaptive robust controller as following formulas based on the adaptive law {dot over (γ)}i and the constraint following error ϵi:

OG Complex Work Unit Math
in this formula, κi meaning a controlling and adjusting parameter which is greater than 0; si1(pi,pi,t) used to handle initial incompatibility problems; si2(γi,pi,pi,t) used to handle the uncertainty and the influence; Ai(pi,t) meaning the constrain matrix of the i'th unmanned system; and
step S6, controlling the plurality of unmanned systems using the constructed adaptive robust controller.