The effect of coincidence horizon on predictive functional control

This paper gives an analysis of the efficacy of PFC strategies. PFC is widely used in industry for simple loops with constraint handling, as it is very simple and cheap to implement. However, the algorithm has had very little exposure in the mainstream literature. This paper gives some insight into when a PFC approach is expected to be successful and, conversely, when one should deploy with caution

The effect of model structure on the noise and disturbance sensitivity of Predictive Functional Control

An Independent Model (IM) structure has become a standard form used in Predictive Functional Control (PFC) for handling uncertainty. Nevertheless, despite its popularity and efficacy, there is a lack of systematic analysis or academic rigour in the literature to justify this preference. This paper seeks to fill this gap by analysing the effectiveness of different prediction models, specifically the IM structure and T-filter, for handling noise and disturbances. The observations are validated via both closed-loop simulation and real-time implementation and show that the sensitivity relationships are system dependent, which in turn emphasises the importance of performing this analysis to ensure a robust PFC implementation

Operation Everest III: energy and water balance

We hypothesized that hypoxia decreases energy intake and increases total energy requirement and, additionally, that decreased barometric pressure increases total water requirement. Energy and water balance was studied over 31 days in a hypobaric chamber at 452-253 Torr (corresponding to 4,500-8,848 m altitude), after 7 days acclimatization at 4,350 m. Subjects were eight men, age 27+/-4 years (mean+/-SD), body mass index 22.9+/-1.5 kg/m(2). Food and water intake was measured with weighed dietary records, energy expenditure and water loss with labelled water. Insensible water loss was calculated as total water loss minus urinary and faecal water loss. Energy intake at normoxia was 13.6+/-1.8 MJ/d. Energy intake decreased from 10.4+/-2.1 to 8.3+/-1.9 MJ/d (

Sensitivity and a Preferable Alternative to Re-aligned Models for Prediction in MPC

Most papers on predictive control use either state space models with an observer or transfer function models with output realignment for prediction purposes. Here it is shown that this approach can have weaknesses, especially with regard to noise rejection and the independent model approach should soften be preferred

Predictive Functional Control of Unstable Processes

Application of predictive functional control (PFC) has been very successful on many processes, however, application to unstable open-loop processes has met more varied success rates. Certain processes in particular with factors of the type (s-a) (s-ra), r-1 have proved very difficult to stabilise. This paper illustrates how the pre-stabilisation approach to prediction can be used to overcome this bottleneck and with the added bonus of retaining the intuitive tuning parameters that make PFC popular

Handling Constraints with Predictive Functional Control of Unstable Processes

This paper tackles 2 major issues. The first is to develop a new means of including constraint handling for unstable processes into the industrial successful and computationally efficient algorithm, predictive functional control (PFC) ; the benefits are illustrated. The second is to show how the technique to be proposed has recursive feasibility in the nominal case, that is feasibility now implies feasibility at the next sampling instant. This is known to be essential for robust stabilisation of unstable processes

Optimal generalized predictive functional control with applications to extended PID control for quadruple tank

Algorithm of optimal Generalized Predictive Functional Control is presented towards the control problem of linear discrete-time state-space multivariable systems. A quadruple tank system is simulated to demonstrate typical results. The proposed controller has been structured in a reduced order arrangement including a set of specified linear transfer-functions along with gains that are found to minimize a GPC cost-index. This approach enables a range of classical controller structures to be used in the feedback loop such as extended PI, PID or Lead-lag or a more general transfer function form. A MATLAB simulation was used to test the performance of the restricted structure controller for regulation and tracking problems and was compared against a classical PI Controller

Input shaping for PFC: how and why?

Predictive functional control (PFC) is a highly successful strategy within industry, but for cases with challenging dynamics the most effective tuning approaches are still an active research area. This paper shows how one can deploy some insights from the more traditional model predictive control literature in order to enable systematic tuning and in particular, to ensure that the key PFC tuning parameter, that is the desired closed-loop time constant, is effective. In addition to enabling easier and more effective tuning, the proposed approach has the advantage of being simple to code and thus retaining the simplicity of implementation and tuning that is a key selling point of PFC. This paper focuses on design for open-loop unstable and also processes with significant under-damping in their open-loop behaviour