Robust Laguerre based model predictive control for trajectory tracking of LTV systems

Jamalabadi, Marzieh; Naraghi, Mohammad; Sharifi, Iman; Firouzmand, Elnaz

doi:10.1109/icee52715.2021.9544190

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…Gonzalez et al [20] designed online tubes for trajectory tracking of a mobile robot, and the execution time was 0.127 s on average (LTV and MIMO). The execution time decreased by 48 % to 0.0653 s by utilizing tube‐based LMPC with lookup tables and time‐varying tubes [25]. Finally, the proposed algorithm declined the execution time significantly to 2.3e−06 s on average, which makes this controller appropriate for fast dynamics and real‐time operations (since simulations were performed by MATLAB, the execution time per step was also measured by MATLAB).…”

Section: Simulationmentioning

confidence: 99%

“…Consequently, this proposed idea in this paper and other research in the field of suboptimal controllers can be immensely beneficial for complex systems. For example, in [23], a type of suboptimal MPC is used to alleviate this burden for a complex and constrained multiagent system, and to reduce the computational complexity of MPC, the authors of [25] implemented a Laguerre-based MPC with a tube-based scheme to track a trajectory by a mobile robot in both the LTI and LTV cases. In this manner, robustness is achieved, constraints are held, and stability is guaranteed.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, only the LMI‐based controller operates online in the proposed algorithm of this paper, as it is much simpler and faster than MPC. It is worth mentioning that there is no need for the computation of invariant sets either offline [25, 27] or online [20] in this suggested method. Consequently, the proposed algorithm does not require solving complex optimizations with long prediction horizons of MPC or computing demanding invariant sets during the operation. The proposed algorithm comprises two controllers: the LMPC controller, and the LMI‐based controller.…”

Section: Introductionmentioning

confidence: 99%

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Robust Laguerre‐based model predictive control for trajectory tracking of a mobile robot using an linear matrix inequality (LMI)‐based approach

Jamalabadi,

Firouzmand,

Sharifi

et al. 2023

Asian Journal of Control

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This paper studies the trajectory tracking of a constrained mobile robot under slippery conditions. The goal is to propose a controller for real‐time operations of time‐varying dynamics with insignificant execution time. Therefore, a Laguerre‐based model predictive control (LMPC) is designed, and robustness is provided with an linear matrix inequality (LMI)‐feedback controller. Moreover, a recursive least square (RLS) algorithm with a forgetting factor is utilized to identify the required parameters of the LMI‐based controller. LMPC and LMI‐based controller stability is achieved with suboptimal theory and Lyapunov function, respectively. This algorithm separates the nominal system and introduces new dynamics containing uncertainties. Furthermore, LMPC is removed from the online calculation, which dramatically reduces computation burden and time; consequently, online computation is dedicated to determining the LMI feedback. Simulations are provided to compare the proposed robust controller to its not robust counterpart. Finally, it is demonstrated that this controller diminishes the execution time considerably, making it incomparable to previous robust MPC strategies.

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Section: Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%