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Application of Sum of Squares Method in Nonlinear H ∞ Control for Satellite Attitude Maneuvers

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  • Fanwei Meng
  • Dini Wang
  • Penghui Yang
  • Guanzhou Xie

Abstract

The Hamilton–Jacobi–Issacs (HJI) inequality is the most basic relation in nonlinear H ∞ design, to which no effective analytical solution is currently available. The sum of squares (SOS) method can numerically solve nonlinear problems that are not easy to solve analytically, but it still cannot solve HJI inequalities directly. In this paper, an HJI inequality suitable for SOS is firstly derived to solve the problem of nonconvex optimization. Then, the problems of SOS in nonlinear H ∞ design are analyzed in detail. Finally, a two-step iterative design method for solving nonlinear H ∞ control is presented. The first step is to design an adjustable nonlinear state feedback of the gain array of the system using SOS. The second step is to solve the L 2 gain of the system; the optimization problem is solved by a graphical analytical method. In the iterative design, a diagonally dominant design idea is proposed to reduce the numerical error of SOS. The nonlinear H ∞ control design of a polynomial system for large satellite attitude maneuvers is taken as our example. Simulation results show that the SOS method is comparable to the LMI method used for linear systems, and it is expected to find a broad range of applications in the analysis and design of nonlinear systems.

Suggested Citation

  • Fanwei Meng & Dini Wang & Penghui Yang & Guanzhou Xie, 2019. "Application of Sum of Squares Method in Nonlinear H ∞ Control for Satellite Attitude Maneuvers," Complexity, Hindawi, vol. 2019, pages 1-10, November.
  • Handle: RePEc:hin:complx:5124108
    DOI: 10.1155/2019/5124108
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    2. khabaz, Mohamad Khaje & Eftekhari, S. Ali & Toghraie, Davood, 2022. "Vibration and dynamic analysis of a cantilever sandwich microbeam integrated with piezoelectric layers based on strain gradient theory and surface effects," Applied Mathematics and Computation, Elsevier, vol. 419(C).
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    4. Man-Wen Tian & Shu-Rong Yan & Jinping Liu & Khalid A. Alattas & Ardashir Mohammadzadeh & Mai The Vu, 2022. "A New Type-3 Fuzzy Logic Approach for Chaotic Systems: Robust Learning Algorithm," Mathematics, MDPI, vol. 10(15), pages 1-20, July.

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