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Multivariable continuous-time generalised predictive control: A state-space approach to linear and nonlinear systems

Multivariable continuous-time generalised predictive control: A state-space approach to linear and nonlinear systems

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The multivariable continuous-time generalised predictive controller (CGPC) is recast in a state-space form and shown to include generalised minimum variance (GMV) and a new algorithm, predictive GMV (PGMV) as special cases. Comparisons are drawn with the exact linearisation methods of nonlinear control, and it is noted that, unlike the transfer function approach, the state-space approach extends readily to the nonlinear case. The resulting state space design algorithms are conceptually and algorithmically simpler than the corresponding transfer function based versions and have been realised as a freely available Matlab tool-box.

Inspec keywords: nonlinear control systems; state-space methods; multivariable control systems; predictive control

Other keywords: state-space approach; Matlab tool-box; transfer function based versions; exact linearisation methods; CGPC; nonlinear systems; nonlinear control; state space design algorithms; generalised minimum variance; multivariable continuous-time generalised predictive control; linear systems; PGMV; predictive GMV

Subjects: Control system analysis and synthesis methods; Optimal control; Nonlinear control systems; Multivariable control systems

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