Linear Time-Varying Robust Model Predictive Control for Discrete-Time Nonlinear Systems

Pereira, Gonçalo Collares; Lima, Pedro F.; Wahlberg, Bo; Pettersson, Henrik; Mårtensson, Jonas

doi:10.1109/cdc.2018.8618866

Cited by 5 publications

(1 citation statement)

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“…Note that the system ( 24) can be converted to a polytopic system with the vertices determined by the known boundary values of uncertainties, and the associated robust stability can be ensured by using the parameter dependent Lyapunov function techniques [44], [45]. Moreover, the high-level EMPC resets the error state to zero every T s time interval because it synchronises the real aircraft state as the new initial state of the future reference trajectory.…”

Section: Proof See Appendix Bmentioning

confidence: 99%

Economic Model-Predictive Control for Aircraft Forced Landing: Framework and Two-Level Implementation

Dong

Jiang

Liu

et al. 2022

IEEE Trans. Aerosp. Electron. Syst.

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This paper presents an optimization-based control framework for the autonomous forced landing of a fixed-wing Unmanned Aircraft (UA). A two-level MPC scheme is proposed to realize this framework, where an EMPC in a long piece-wise constant fashion is proposed at the high-level while a short fixedhorizon linear time-varying MPC at the low-level responds to fast dynamics of UA and tracks the optimal path provided by the high-level controller, alleviating computational burden compared to the high frequency single-layer MPC scheme. Comparing with single EMPC setup with high sampling frequency, this hierarchical EMPC controller can significantly reduce the computational complexity and make it feasible to be implemented in realtime. In addition, it also responds to disturbances (e.g. wind) and aircraft fast dynamics in a timely manner. The recursive feasibility and stability of the high and low-level MPC schemes are established. The performance of the proposed EMPC forced landing function is illustrated by simulation case studies on both Aerosonde and Skywalker X8, compared favorably with competing schemes.

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Section: Proof See Appendix Bmentioning

confidence: 99%