Predictive controlFuzzy controlFuzzy modelsThis paper presents the application of a combined control strategy grounded in a basic Model Predictive Control (MPC) structure, but using a Discrete Fuzzy Model (DFM) of the process in the state space domain. Two methods of optimization are tested. The ...
In this work, two efficient robust fuzzy model predictive control algorithms are investigated for discrete nonlinear systems with multiple time delays and bounded disturbances. The famous T-S fuzzy systems are utilized to represent nonlinear systems. Instead of Lyapunov-Krasovskii functional, Lyapunov-Razu...
In this paper, an adaptive fuzzy model predictive control is developed for networked unknown nonlinear systems which are modeled by an interval type-2 (IT-2) Takagi–Sugeno (T–S) fuzzy method. By taking the effects of delay and packet loss occurrence in both network links as well as distur...
On the other hand, model predictive control (MPC) and dynamic programming strategies require future information or a prediction of the FC–HEV’s driving cycle, such as the trajectory, the speed, or the load power. In this case, the power distribution poses an optimization problem and requires...
The Takagi–Sugeno (T–S) fuzzy model is a versatile approach widely used in system control, often in combination with other strategies. This paper addresses key control challenges linked to the T–S system and presents important considerations to ensure
Aimed at a multi-channel loading system, a fuzzy model based predictive control with multi-step linearization scheme is proposed. Using a Takagi-Sugeno fuzzy model as a predictive model of the loading system, a linearized fuzzy model with multi-step, the predictive control is applied to the loa...
This prescriptive approach is closely related to predictive control. The formulation of the control problem as a confluence of fuzzy goals and fuzzy constraints leads to a generalization of the objective function used in model-based predictive control. This cost function is usually a sum of an ...
This paper is concerned with the control of an AUV. A model predictive controller is developed herein where the traditional cost function has been replaced by a fuzzy performance index which represent the goals and constraints of the problem. Since fuzzy logic is basically derived from knowledge ...
In [21], a fuzzy model predictive control (FMPC) system is designed by using a fuzzy convolution model for a highly nonlinear process. In [22], a self-organizing fuzzy logic controller (SOFLC) is proposed. The fuzzy rules are generated on-line by using a Takagi–Sugeno–Kang (TSK)-...
And a T-S fuzzy model predictive control strategy is then developed. The controller is validated with a wind turbine simulator. The results have shown better performance in comparison with existing controllers. 展开 DOI: 10.1051/e3sconf/20187201008 年份: 2018 ...