Event-Based MPC for Nonlinear Systems with Additive Disturbances: A Quasi-Differential Type Approach

Xu, Zhongxian; He, Ning; He, Lei; Ma, Kai

doi:10.1016/j.isatra.2021.11.009

Cited by 11 publications

(4 citation statements)

References 19 publications

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“…Alternatively, one may examine the benefit of using a sub-optimal solution from a quadratic programming solver, as often in practice the sub-optimal solution gives satisfactory results [18]. In the limit, a non-periodic sampling of the control action, e.g., triggered by events such as context changes beyond tolerance intervals, can significantly reduce the overall computational cost [24].…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

Ergonomic and Economic Office Light Level Control

et al. 2022

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Light regulation systems in industrial or office buildings play an important role in minimizing the use of fossil energy resources, while providing both economic and ergonomic optimal functionality. Although industrial buildings resolve the problem of interaction or disturbance mitigation by providing constant light levels exclusively from artificial sources, office landscapes may benefit from up to a 20% decrease in costs if mixed light sources are optimized properly. In this paper, we propose a theoretical framework based on model predictive control (MPC) to resolve a multi-system with strong dynamic interactions and multi-objective cost optimization. Centralized and distributed predictive control strategies are compared on various office landscaping structures and functionality conditions. Economic and ergonomic indexes are evaluated in a scaled laboratory setting.

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Section: Multi-objective Optimizationmentioning

confidence: 99%

Ergonomic and Economic Office Light Level Control

et al. 2022

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“…Inspired by the studies in [11], [29] and our preliminary work [30], a state-dependent triggering mechanism is proposed in this part, namely the gradient-based event-driven triggering mechanism. In general, due to the additive disturbances, the real state x(t|t ζ ) and the optimal state x * (t|t ζ ) cannot match with each other.…”

Section: B Gradient-based Event-driven Triggering Mechanismmentioning

confidence: 99%

A Gradient-Based Event-Driven MPC for Nonlinear Systems With Additive Disturbances Using State-Dependent Thresholds

2022

IEEE Access

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In this article, we propose a gradient-based event-driven model predictive control (GEMPC) algorithm with a state-dependent threshold for nonlinear systems with additive disturbances and input and state constraints. Firstly, a novel gradient-based event-driven strategy is constructed in the light of the error gradient between the optimal prediction of the state and the real one, which could ensure the Zeno-free property via a positive triggering interval. Subsequently, the novel triggering mechanism and the dualmode control are combined to establish a GEMPC framework, to further reduce the computing burden and communication transmission especially when the computational resources are limited. Additionally, the feasibility of the GEMPC algorithm and the input-to-state practical stability (ISpS) property of the considered system have been strictly proved in theory. Finally, the simulation comparison results on control of a perturbed nonlinear system are utilized to show the validity of the GEMPC algorithm.INDEX TERMS Event-driven control, model predictive control (MPC), gradient-based mechanism, constrained systems, state-dependent threshold.

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“…However, such a strategy will cause a waste of computing and communication resources. [13][14][15] To address this challenge, event-triggered control (ETC) has been introduced into the MPC framework in recent years. 16 Different from the conventional time-triggered MPC, the event-triggered MPC (ETMPC) solves the optimal control problem when specified events are satisfied.…”

Section: Introductionmentioning

confidence: 99%

“…In the conventional MPC, the optimal control problem needs to be solved at every sampling time. However, such a strategy will cause a waste of computing and communication resources 13‐15 . To address this challenge, event‐triggered control (ETC) has been introduced into the MPC framework in recent years 16 .…”

Section: Introductionmentioning

confidence: 99%

Dual‐mode event‐triggered predictive control for nonlinear systems with bounded disturbances

Du,

Zhao,

Wang

et al. 2023

Intl J Robust & Nonlinear

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In this article, we propose a dual‐mode event‐triggered predictive control method for nonlinear systems with bounded disturbances. The proposed method contains two triggering mechanisms, namely, the hybrid threshold‐based event‐triggered model predictive control (HETMPC) mechanism and the event‐triggered linear quadratic regulator mechanism. The former triggering mechanism is designed based on the error between the real state and the optimal state and also the disturbance information acted on the investigated system. Compared with the traditional fixed triggering threshold, the designed HETMPC has a fewer triggering numbers and reduces the computational burden of online real‐time optimization. This event‐triggered mechanism will be adopted before the states go into the terminal invariant set. The latter event‐triggered mechanism is designed based on the derivation of the system state and it will be adopted after the states enter the terminal invariant set. The feasibility and the input‐to‐state practical stability analysis of the designed strategy is presented. Some simulations, including the application to a mass‐spring‐damper system, are provided to show the correctness and feasibility of the designed algorithms.

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Event-Based MPC for Nonlinear Systems with Additive Disturbances: A Quasi-Differential Type Approach

Cited by 11 publications

References 19 publications

Ergonomic and Economic Office Light Level Control

Ergonomic and Economic Office Light Level Control

A Gradient-Based Event-Driven MPC for Nonlinear Systems With Additive Disturbances Using State-Dependent Thresholds

Dual‐mode event‐triggered predictive control for nonlinear systems with bounded disturbances

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