Efficient Model-Predictive Control for Networked Interval Type-2 T–S Fuzzy System With Stochastic Communication Protocol

Dong, Yuying; Song, Yan; Wei, Guoliang

doi:10.1109/tfuzz.2020.3004192

Cited by 47 publications

(18 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A similar approach is used for ( 19 ) and ( 20 ). This approach is different from the traditional linear matrix inequalities-based MPC design [ 23 , 24 , 35 , 37 ]. It has also been shown in existing literature [ 19 , 20 , 22 , 44 – 46 ] that the linear programming approach is more effective in coping with the positivity of positive systems than linear matrix inequalities.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Event-triggered model predictive control of positive systems with random actuator saturation

Zhang

Lin

2021

Nonlinear Dyn

View full text Add to dashboard Cite

This paper investigates the event-triggered model predictive control of positive systems with actuator saturation. Interval and polytopic uncertainties are imposed on the systems, respectively. First, a new model with actuator saturation obeying Bernoulli distribution is established, which is more general and powerful for describing the saturation phenomenon than the saturation in a deterministic way. Then, a linear event-triggering condition is constructed based on the state and error signal. Under the event-triggering condition, an interval estimate approach is presented to reach the positivity and stability of the systems. The saturation part in the controller is technically transformed into a non-saturation part. Thus, a linear programming approach is proposed to compute the event-triggered controller gain and the corresponding gain of attraction domain. A predictive algorithm is introduced for the computation of the event-triggered controller parameters. Finally, an example is provided to illustrate the validity of the design.

show abstract

Section: Resultsmentioning

confidence: 99%

“…This class of systems has been extensively applied for describing time-varying systems and nonlinear systems. Many MPC literature also used polytopic uncertain systems to model practical dynamical processes [ 23 , 24 , 50 ]. Interval uncertain systems are another important modeling method for uncertain systems.…”

Section: Problem Formulationmentioning

confidence: 99%

Event-triggered model predictive control of positive systems with random actuator saturation

Zhang

Lin

2021

Nonlinear Dyn

View full text Add to dashboard Cite

show abstract

“…Our proposed results can be readily extended to more general systems, such as uncertain systems 17 and T-S fuzzy systems. 11,34 In this article, the techniques handling the time delay are conservative to a certain extent. By incorporating the augmented L-K functionals and some advanced inequalities, 8,12 we can obtain less conservative conditions, which is our future work.…”

Section: Discussionmentioning

confidence: 99%

“…32 In the past few years, the analysis and synthesis problems for NCSs under various communication protocols have gained significant attention and some pioneering results have been reported. [33][34][35][36][37][38][39][40][41][42] For example, in Reference 37, the stability and L 2 -gain analysis problems have been studied for NCSs with communication delays under the RR protocol and, in Reference 42, the moving horizon estimation problem has been addressed for networked systems with state delays under the RR protocol. However, it is worth mentioning that the phenomenon of actuator saturations has been largely overlooked in most existing literature.…”

Section: Introductionmentioning

confidence: 99%

Dynamic output‐feedback control for discrete time‐delayed systems with actuator saturations under round‐robin communication protocol

Chen

Wang

Alsaadi

et al. 2021

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

In this article, the dynamic output-feedback H ∞ control problem is investigated for discrete-time state-delay systems subject to exogenous disturbances and actuator saturations under the round-robin communication protocol. Using the switched system approach, the Lyapunov-Krasovskii functional and the modified sector condition, sufficient conditions are first obtained under which the closed-loop systems can achieve some desirable performance indices such as the boundedness, the H ∞ performance and the stability in the absence of disturbances. Then, the controller is explicitly characterized by means of the solvability of linear matrix inequalities. For the case without time delays, the corresponding conditions are also presented. Subsequently, the optimization problems about the performance indices are discussed. Finally, the benefit and effectiveness of the proposed results are specifically illustrated via two simulation examples.

show abstract

“…Through simulating the interactions among the individuals in the fish schooling or bird flocking, the particle swarm optimization (PSO) algorithm has been presented in [16] with the purpose of exploring the searching space, which is made possible by automatically adjusting the current velocities and the current positions of the particles according to the competition and cooperation among the particles. Serving as a powerful evolutionary technique, the PSO algorithm is capable of discovering the globally optimal solution in an efficient yet effective way in the research areas of parameter optimization, neural network training, clustering analysis, combination optimization, pattern recognition, image processing and so forth [1,5,6,8,17,20,22,30,32,36,41,46,50].…”

Section: Introductionmentioning

confidence: 99%

A novel PID-like particle swarm optimizer: on terminal convergence analysis

Wang

Han

et al. 2021

Complex Intell. Syst.

View full text Add to dashboard Cite

In this paper, a novel proportion-integral-derivative-like particle swarm optimization (PIDLPSO) algorithm is presented with improved terminal convergence of the particle dynamics. A derivative control term is introduced into the traditional particle swarm optimization (PSO) algorithm so as to alleviate the overshoot problem during the stage of the terminal convergence. The velocity of the particle is updated according to the past momentum, the present positions (including the personal best position and the global best position), and the future trend of the positions, thereby accelerating the terminal convergence and adjusting the search direction to jump out of the area around the local optima. By using a combination of the Routh stability criterion and the final value theorem of the Z-transformation, the convergence conditions are obtained for the developed PIDLPSO algorithm. Finally, the experiment results reveal the superiority of the designed PIDLPSO algorithm over several other state-of-the-art PSO variants in terms of the population diversity, searching ability and convergence rate.

show abstract

Efficient Model-Predictive Control for Networked Interval Type-2 T–S Fuzzy System With Stochastic Communication Protocol

Cited by 47 publications

References 36 publications

Event-triggered model predictive control of positive systems with random actuator saturation

Event-triggered model predictive control of positive systems with random actuator saturation

Dynamic output‐feedback control for discrete time‐delayed systems with actuator saturations under round‐robin communication protocol

A novel PID-like particle swarm optimizer: on terminal convergence analysis

Contact Info

Product

Resources

About