This paper gives new insight and design proposals for Predictive Functional Control (PFC) algorithms. Common practice and indeed a requirement of PFC is to select a coincidence horizon greater than one for high-order systems and for the link between the design parameters and the desired dynamic to be weak. Here the proposal is to use parallel first-order models to form an independent prediction model and show that with these it is possible both to use a coincidence horizon of one and moreover to obtain precisely the desired closed-loop dynamics. It is shown through analysis that the use of a coincidence horizon of one greatly simplifies coding, tuning, constraint handling and implementation. The paper derives the key results for high-order ...
Despite is popularity in industry and obvious efficacy, Predictive Functional Control has few rigoro...
Predictive Functional Control (PFC) is a heuristic Model Predictive Control (MPC) algorithm that off...
This paper presents two significant contributions to the understanding of Predictive Functional Cont...
Predictive functional control (PFC) has emerged as a popular industrial choice owing to its simplici...
This paper presents the new algorithm of PP-PFC (Pole-placement Predictive Functional Control) for ...
This paper presents the new algorithm of PP-PFC (Pole placement Predictive Functional Control) for s...
This paper gives an analysis of the efficacy of PFC strategies. PFC is widely used in industry for s...
Predictive functional control (PFC) is a cheap and simplified model predictive controller, which com...
Predictive functional control (PFC) is a fast and effective controller that is widely used for proce...
This thesis presents a development and analysis of a low computation Model Predictive Control (MPC) ...
Predictive functional control (PFC) is a straightforward and cheap model-based technique for systema...
Predictive functional control (PFC) is the simplest model-based algorithm, equipped with the attribu...
Predictive Functional Control (PFC), a simplified and low-cost MPC algorithm, has gained considerabl...
Predictive functional control (PFC) is a fairly straightforward model-based technique for controllin...
This paper presents a novel modification and insights in the topic of predictive functional control ...
Despite is popularity in industry and obvious efficacy, Predictive Functional Control has few rigoro...
Predictive Functional Control (PFC) is a heuristic Model Predictive Control (MPC) algorithm that off...
This paper presents two significant contributions to the understanding of Predictive Functional Cont...
Predictive functional control (PFC) has emerged as a popular industrial choice owing to its simplici...
This paper presents the new algorithm of PP-PFC (Pole-placement Predictive Functional Control) for ...
This paper presents the new algorithm of PP-PFC (Pole placement Predictive Functional Control) for s...
This paper gives an analysis of the efficacy of PFC strategies. PFC is widely used in industry for s...
Predictive functional control (PFC) is a cheap and simplified model predictive controller, which com...
Predictive functional control (PFC) is a fast and effective controller that is widely used for proce...
This thesis presents a development and analysis of a low computation Model Predictive Control (MPC) ...
Predictive functional control (PFC) is a straightforward and cheap model-based technique for systema...
Predictive functional control (PFC) is the simplest model-based algorithm, equipped with the attribu...
Predictive Functional Control (PFC), a simplified and low-cost MPC algorithm, has gained considerabl...
Predictive functional control (PFC) is a fairly straightforward model-based technique for controllin...
This paper presents a novel modification and insights in the topic of predictive functional control ...
Despite is popularity in industry and obvious efficacy, Predictive Functional Control has few rigoro...
Predictive Functional Control (PFC) is a heuristic Model Predictive Control (MPC) algorithm that off...
This paper presents two significant contributions to the understanding of Predictive Functional Cont...