This paper proposes a novel economic requirements-oriented online tuning strategy for
MPC, the design of which encompasses the well-known operational particularities of oil …

Goal: We propose novel supervised control architectures to regulate the cognitive stress
state and close the loop. Methods: We take information present in underlying neural …

Abstract Functional Electrical Stimulation (FES) on muscles can recover voluntary motions of
the upper limb paralysed patients, enabling them to conduct daily life activities like grasping …

In this paper, an extension of the modified generalized predictive control (GPC) algorithm
and a tuning strategy is presented. To take the plant dynamics such as under damped …

This research paper focuses on the design and development of simplified RTDA control law
computation formulae for SOPDT process with minimum or non-minimum zero. The design …

The proposed auto-tuning method is a layer of receding horizon optimization problem
whose objective function is able to consider the performance/robustness through the trade …

In this work, the recursive least squares (RLS) algorithm, which traditionally was used in the
generalized predictive controller (GPC) framework solely for model adaptation purposes …

A direct adaptive tuning strategy is proposed for model predictive controllers. Parameter
tuning is essential for a satisfactory control performance. Various tuning methods are …

Dynamic Matrix Control (DMC) is a widely used model predictive controller (MPC) in
industrial plants. The successful implementation of DMC in practical applications requires a …

This paper presents a new tuning strategy for Generalized Predictive Controllers (GPC)
based on Analysis of Variance (ANOVA). This strategy is derived for Second Order plus …