The objective of life extending control (LEC), also known as damage mitigating control, is to design a controller to achieve a good tradeoff between structural durability and dynamic performance in a system. In this paper, continuum fatigue damage theory for a boiler system is discussed. To reduce the accumulated damage, a variance constrained model predictive control (VCMPC) problem is develop...

In this paper we develop a Model Predictive Controller (MPC) for regulation of a cement mill circuit. The MPC uses soft constraints (soft MPC) to robustly address the large uncertainties present in models that can be identified for cement mill circuits. The uncertainties in the linear predictive model of the cement mill circuit stems from large variations and heterogeneities in the feed materia...

A new approach to the design of Model Predictive Controller (MPC) that simultaneously addresses the actuator saturation and backlash is proposed in this paper. The discrete characteristics of the actuator backlash allows one to reformulate the input constraints as a set of mixed integer linear inequalities. As a result, the MPC is designed by solving a Mixed-integer Quadratic Programming proble...

Model Predictive Control (MPC) strategies are typically implemented in two levels: a steady-state target calculation and a control calculation. The steady-state target calculation consumes excess degrees of freedom within the control problem to provide optimal steady-state performance with respect to some specified objective. In some MPC approaches, the target calculation is formulated as a Lin...

Subspace predictive control (SPC) is recently seen in the literature for joint system identification and control design. This combination enables automatically tuning the parameters in conventional model predictive control (MPC); and therefore provides a solution to the problem of fault tolerant MPC design. The existing SPCs either deal with open-loop data or depend on the information of the co...

Two new contributions are presented here. This paper proposes using a Model Predictive Control (MPC) incorporating a Radial Basis Function (RBF) Network Observer for the fuel injection problem. Firstly a RBF Network is used as an observer for the volumetric efficiency of the air system. This allows for gradual adaptation of the observer, ensuring the control scheme is capable of maintaining goo...

Abstract: This paper proposes a discrete-time adaptive model predictive control (MPC) algorithm for a class of constrained linear time-invariant systems subject to state-dependent disturbances, which updates the estimate of uncertain system parameters on-line and produces the control input ensuring the constraint fulfillment. This method is based on an adaptive mechanism and a robust MPC algori...

We survey some recent research directions within the field of approximate dynamic programming, with a particular emphasis on rollout algorithms and model predictive control (MPC). We argue that while they are motivated by different concerns, these two methodologies are closely connected, and the mathematical essence of their desirable properties (cost improvement and stability, respectively) is...

Solutions to constrained linear model predictive control (MPC) problems can be pre-computed off-line in an explicit form as a piecewise linear (PWL) state feedback defined on a polyhedral partition of the state space. This admits implementation at high sampling frequencies in real-time systems with high reliability and low software complexity. Recently, algorithms that determine an approximate ...

Explicit MPC of constrained linear systems is known to result in a piecewise affine controller and therefore also piecewise affine closed loop dynamics. The complexity of such analytic formulations of the control law can grow exponentially with the prediction horizon. The suboptimal solutions offer a trade-off in terms of complexity and several approaches can be found in the literature for the ...