Real-Time Reachable Set Control for Neutral Singular Markov Jump Systems With Mixed Delays

Self Cite

This article investigates the active disturbance rejection‐based distributed event‐triggered bipartite consensus problem of nonaffine nonlinear multiagent systems with input saturation. To reduce the update frequency of the control signal, an event‐triggered mechanism is employed for each follower. Additionally, the active disturbance rejection technology, as a combination of the extended state observer and the tracking differentiator, is introduced to estimate the uncertainties of the system and address the problem of explosion of complexity in the backstepping design process. Compared with the traditional distributed bipartite consensus schemes using neural networks/fuzzy logic systems, the design complexity of the control law is reduced in the proposed scheme. Meanwhile, the tracking error is maintained within a predefined range via the funnel function. Finally, the stability of the system is proved under the Lyapunov stability analysis theory, and the effectiveness of the proposed strategy is verified via simulation examples.

“…Lemma 3 (see the works of Zhang et al 40,41 ). Suppose (Φ − 1)(K − 1) = 1, where Φ > 1 and K > 1, then for ∀𝜉 ∈ R n , ∀𝜙 ∈ R n and 𝜔, the following inequality holds…”

Section: Theoretical Basis Of Adrcmentioning

confidence: 99%

Section: Tracking Control Designmentioning

confidence: 99%

Active disturbance rejection‐based event‐triggered bipartite consensus control for nonaffine nonlinear multiagent systems

Cao

Niu

Zong

et al. 2023

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“…This kind of desired control scheme has a strong robustness and anti-interference capability, which is necessary to guarantee the work safety for the target system with a combination of both theoretical and practical significance. Therefore, the issue of the RSS associated with different systems has attracted many attention of scholars in the past decades, such as neural network systems, 34,35 singular systems, 31,36 time-delay systems, 37,38 and switched systems. 39,40 Besides, the article 41 investigates the RSS issue of MJSs with time-varying delays subject to the hidden Markov model (HMM) and general transition probabilities.…”

Section: Introductionmentioning

confidence: 99%

Hidden Markov model‐based approach on real‐time output reachable set synthesis for discrete‐time nonlinear Markovian jump systems

Feng

et al. 2023

This note addresses the asynchronous state-feedback control (ASC) for delay nonlinear Markovian jump systems (DNMJSs) subject to reachable set boundary. Under taking time-varying delays and external disturbance into consideration, Takagi-Sugeno fuzzy model is adopted to approximate the nonlinear dynamics systems. Although the assumption about time-delay is practical, it will cause subsystem modes to be not synchronous with the controller modes. As a consequence, the description method of the nonsynchronous phenomenon is introduced, which is a hidden Markov model. Furthermore, an available ASC is designed and all reachable states of the system is constrained within the compact ellipsoidal boundary to guarantee the safe operation of the DNMJSs. The existence conditions of the desired ASC are obtained via solving a group of feasible linear matrix inequalities. Finally, some numerical simulations are provided to verify the availability of the proposed method in this article.

“…Although this mode could transmit control signals to the actuator in real‐time, it is likely to lead to excessive consumptions of both communication and computation resources 34‐39 . Different from the time‐triggered control, the event‐triggered control determines online when to communicate by a triggered mechanism, updating the values of control inputs only if the deviation between the current state and the desired state exceeds a predefined threshold 40‐44 . In this sense, the event‐triggered control is more advantageous in communication efficiency and has been employed for improving control law design of fractional‐order nonlinear systems 45 .…”

Section: Introductionmentioning

confidence: 99%

“…[34][35][36][37][38][39] Different from the time-triggered control, the event-triggered control determines online when to communicate by a triggered mechanism, updating the values of control inputs only if the deviation between the current state and the desired state exceeds a predefined threshold. [40][41][42][43][44] In this sense, the event-triggered control is more advantageous in communication efficiency and has been employed for improving control law design of fractional-order nonlinear systems. 45 Note that, most event-triggered control approaches are based on static threshold conditions, being set as a predefined constant, which cannot reach requirements in certain practical cases particularly while the current state deviates the desired state considerably in short periods.…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered adaptive tracking control for uncertain fractional‐order nonstrict‐feedback nonlinear systems via command filtering

Wang

Zhao

et al. 2022

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This article puts forward an event-triggered adaptive neural tracking control strategy for a class of uncertain fractional-order nonstrict-feedback nonlinear systems with full-state constraints and dead-zone inputs. The proposed control strategy is capable of surmounting an inherent shortcoming in most traditional backstepping control approaches which results from the repeated differentiation of virtual control functions, and enhancing the transmission efficiency of control signals by introducing an event-triggered mechanism with a dynamic threshold condition. Furthermore, by constructing a novel barrier Lyapunov function in each step of the backstepping procedure, the design difficulty arising from the system state constraints issue under fractional-order cases is resolved. It is strictly proved that the tracking error can converge into a desired small neighborhood of the origin and all signals in the closed-loop system are bounded. Finally, a simulation example is given to verify the effectiveness of our proposed control strategy.