The dynamical characteristics of a gyrostat system with intermittent forcing are investigated, the main work and contributions are given as follows: (1) The gyrostat system with an intermittent forcing is studied, and its dynamical characteristics are investigated by the corresponding Lyapunov exponent spectrums and bifurcation diagrams with respect to the amplitude of intermittent forcing. The modified gyrostat system exists chaotic motion when the amplitude of intermittent forcing belongs to a certain interval, and it can be at a state of stable point or periodic motion by the design of amplitude. (2) The gyrostat system with multiple intermittent forcings is also investigated through the combination of Lyapunov exponent spectrums and bifurcation diagrams, and it behaves periodic motion or chaotic motion when the amplitude or forcing width is different. (3) By the selection of parameters in intermittent forcings, the modified gyrostat system is at a state of stable point, periodic motion or chaotic motion. Numerical simulations verify the feasibility and effectiveness of the modified gyrostat system.
KuangJTanSArichandranK, et al. Chaotic dynamics of an asymmetrical gyrostat. Int J Nonlin Mech2001; 36: 1213–1233.
2.
ChenLQLiuYZ.Chaotic attitude motion of a magnetic rigid spacecraft and its control. Int J Nonlin Mech2002; 37: 493–504.
3.
TongXTabarrokBRimrottFPJ. Chaotic motion of an asymmetric gyrostat in the gravitational field. Int J Nonlin Mech1995; 30: 191–203.
4.
KuangJTanSHLeungAYT. Chaotic attitude motion of satellites under small perturbation torques. J Sound Vib2000; 235: 175–200.
5.
ZwölferABischofG.Modelling and analysis of a gyrostat elastically attached to a vehicle. Veh Syst Dyn2019; 57: 815–840.
6.
PengJLiuY.Chaotic motion of a gyrostat with asymmetric rotor. Int J Nonlin Mech2000; 35: 431–437.
7.
CaiJWuXChenS.Synchronization criteria for non-autonomous chaotic systems via sinusoidal state error feedback control. Phys Scr2007; 75: 379–387.
8.
AghababaMPAghababaHP.Synchronization of nonlinear chaotic electromechanical gyrostat systems with uncertainties. Nonlin Dyn2012; 67: 2689–2701.
9.
CaiJMaM.Synchronization between two non-autonomous chaotic systems via intermittent control of sinusoidal state error feedback. Optik2017; 130: 455–463.
10.
WangZWuH.Stabilization in finite time for fractional-order hyperchaotic electromechanical gyrostat systems. Mech Syst Signal Pr2018; 111: 628–642.
11.
KuangJTanSArichandranK, et al. Chaotic attitude motion of gyrostat satellite via Melnikov method. Int J Bifur Chaos2001; 11: 1233–1260.
12.
SinghSAraújoAD.Asymptotic reproducibility in nonlinear systems and attitude control of gyrostat. IEEE Trans Aerosp Electron Syst1984; 20: 94–103.
13.
FaraminMAtaeiM.Chaotic attitude analysis of a satellite via Lyapunov exponents and its robust nonlinear control subject to disturbances and uncertainties. Nonlin Dyn2015; 83: 361–374.
14.
NikolovSNedkovaN.Gyrostat model regular and chaotic behavior. J Theor Appl Mech2015; 45: 15–30.
15.
AbtahiSMSadatiSHSalariehH.Nonlinear analysis and attitude control of a gyrostat satellite with chaotic dynamics using discrete-time LQR-OGY. Asian J Control2016; 18: 1845–1855.
16.
AbtahiSM.Melnikov-based analysis for chaotic dynamics of spin-orbit motion of a gyrostat satellite. Proc IMechE, Part K: J Multi-Body Dynamics2019; 233: 931–941.
17.
QiGYangX.Modeling of a chaotic gyrostat system and mechanism analysis of dynamics using force and energy. Complexity2019; 2019: 5439596.
18.
HamidzadehSMZarringhalamA.Attitude control of chaotic satellite with unknown input and uncertainties based on sliding control. Int J Comput Appl2014; 97: 32–36.
19.
AbtahiSMSadatiSH.Chaos control in attitude dynamics of a gyrostat satellite based on linearised Poincaré’ map estimation by support vector machine. Proc IMechE, Part K: J Multi-Body Dynamics2013; 227: 302–312.
20.
LiuYZChenLQ.Chaos in attitude dynamics of spacecraft. Berlin: Springer, 2013.
21.
ÇavuşoğluÜKaçarSPehlivanI, et al. Secure image encryption algorithm design using a novel chaos based S-box. Chaos Solit Fract2017; 95: 92–101.
22.
PreishuberMHütterTKatzenbeisserS, et al. Depreciating motivation and empirical security analysis of chaos-based image and video encryption. IEEE Trans Inform Foren Sec2018; 13: 2137–2149.
23.
HeJCaiJ.Design of a new chaotic system based on Van Der Pol oscillator and its encryption application. Mathematics2019; 7: 743–712.
24.
ÇavuşoğluÜKaçarSZenginA, et al. A novel hybrid encryption algorithm based on chaos and S-AES algorithm. Nonlin Dyn2018; 92: 1745–1759.
25.
Silva-GarcíaVMFlores-CarapiaRRentería-MárquezC, et al. Substitution box generation using chaos: an image encryption application. Appl Math Comput2018; 332: 123–135.
26.
LinZYuSLüJ, et al. Design and ARM-embedded implementation of a chaotic map-based real-time secure video communication system. IEEE Trans Circ Syst Vid Technol2015; 25: 1203–1216.
27.
KuoHLiaoTYanJ.Design and synchronization of master-slave electronic horizontal platform system. Discr Dyn Nat Soc2012; 2012: 948126.
28.
YangTChuaLO.Secure communication via chaotic parameter modulation. IEEE Trans Circ Syst I Fund Theor Appl1996; 43: 817–819.
29.
SongYYuX. Multi-parameter modulation for secure communication via Lorenz chaos. In: Proceedings of the 39th IEEE conference on decision and control, Sydney, NSW, Australia, 12–15 December 2000. New York: IEEE.
30.
HeJCaiJ.Parameter modulation for secure communication via the synchronization of Chen hyperchaotic systems. Syst Sci Control Eng2014; 2: 718–726.
31.
ZhouHZhangYLiW.Synchronization of stochastic Lévy noise systems on a multi-weights network and its applications of Chua’s circuits. IEEE Trans Circ Syst I Fund Theor Appl2019; 66: 2709–2722.
32.
YaoXZhouHLiWX.Stabilization of stochastic delayed systems with Lévy noise on networks via periodically intermittent control. Int J Control2018; 93: 1–24.
33.
GeZMLeeCIChenHH, et al. Nonlinear dynamics and chaos control of a damped satellite with partially-filled liquid. J Sound Vib1998; 217: 807–825.
34.
GeZMLinTN.Chaos, chaos control and synchronization of a gyrostat system. J Sound Vib2002; 251: 519–542.
35.
BalcerzakMDabrowskiABlazejczyk-OkolewskaB, et al. Determining Lyapunov exponents of non-smooth systems: perturbation vectors approach. Mech Syst Signal Pr2020; 141: 106734.
36.
ParkerTChuaL.Practical numerical algorithms for chaotic systems. New York: Springer, 1989.
37.
BaierGKleinM.A chaotic hierarchy. Singapore: World Scientific, 1991.
