State estimation and the equivalence of the regulatory and supervisory predictive control law

This paper discusses the effect of state estimation on the equivalence between the regulatory and supervisory predictive control strategies for linear time invariant systems. The analysis presented here shows that in the presence of model-system mismatch, the use of a state estimator rather than the actual state in the feedback loop does not affect the equivalence between the two strategies

Predictive PID controller design

A polynomial predictive optimal control problem is discussed for the discrete time system where the structure of the controller is assumed to be limited to a discrete PID controller. The theoretical problem to be considered is to obtain the causal, stabilising, controller of the pre-specified PID form that minimises a generalised predictive control criterion and is equivalent to a GPC control law. The underlying practical problem and aim of the work is to obtain the optimal PID controller coefficients that provide the required closed loop performance over a range of operating conditions and working point

Multivariable PID controller design using online generalised predictive control optimisation

A novel multivariable state-space predictive PID optimal control law is proposed which is mathematically equivalent to generalised predictive control (GPC). The theoretical problem to be considered is to obtain the causal, stabilising, controllers of pre-specified PID structure, such that the individual PID controllers satisfy a multivariable predictive criterion and hence collectively perform as a multivariate GPC controller. The underlying practical problem and aim of this work is to obtain and develop an online optimisation method for tuning PID controllers so that they can operate either as classical PID controllers or in unison as a multivariable GPC controller. It is shown that such an approach leads to a dual mode controller which is the ability to switch the multivariable PID between operating either as a classical PID controller or a GPC controller

Application of process control loop benchmarking to an oil production platform

A complex system usually comprises numerous loops that are controlled by local SISO controllers. The decision to retune or replace any one of these controllers should be based on an investigation as to whether a change will improve the performance. Such a procedure is referred to as benchmarking. With a benchmarking tool, the engineer can justify a proposed retuning of the controller, since it provides a measure for the quality of control achieved. In this paper, first, the basic theory on minimum variance control is presented. Then, the results that are arising from this theory, and directly applicable to benchmarking, are given. Finally, application of the given ideas to an industrial example, namely a Separation Vessel in an Oil Platform, is described

Restricted structure control loop performance assessment and benchmarking

The problem of restricted-structure benchmarking for multi-input, multi-output (MIMO) systems controlled by multi-loop PID controllers is formulated in state space. The particular criterion shown in this paper is that for a linear quadratic generalised predictive controller, which combines the properties of linear quadratic Gaussian with those of generalized predictive control

NLQGPC predictive PID controller design for MIMO and SISO systems

This paper looks at NLQGPC predictive PID controller design for MIMO and SISO system