Real-time suboptimal model predictive control using a combination of explicit MPC and online optimization
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The process industries are characterized by a large number of continuously operating plants, for which optimal operation is of economic importance. However, optimal operation is particularly difficult to achieve when the process model used in the optimizat ...
In symmetric multilevel inverters, there is a tradeoff between the output quality and the reliability and efficiency of the converter. New asymmetric and hybrid solutions, using different voltages and devices in various parts of the inverter, promise signi ...
A predictive optimal control system for micro-cogeneration in domestic applications has been developed. This system aims at integrating stochastic inhabitant behavior and meteorological conditions as well as modeling imprecisions, while defining operation s ...
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Model predictive control (MPC) is a very effective approach to control nonlinear systems, especially when the systems are high dimensional and/or constrained. MPC formulates the problem of input trajectory generation as an optimization problem. However, du ...
A predictive optimal control system for micro-cogeneration in domestic applications has been developed. This system aims at integrating stochastic inhabitant behavior and meteorological conditions as well as modelling imprecisions, while defining operation ...
The k-set-agreement problem consists for a set of n processes to agree on less than k among n possibly different Values, each initially known to only one process. The problem is at the heart of distributed computing and generalizes the celebrated consensus ...
Convex parameterization of fixed-order robust stabilizing controllers for systems with polytopic uncertainty is represented as an LMI using KYP Lemma. This parameterization is a convex inner-approximation of the whole non- convex set of stabilizing control ...
We consider the problem of distributed estimation, where a set of nodes are required to collectively estimate some parameter of interest. We motivate and propose new versions of the diffusion LMS algorithm, including a version that outperforms previous sol ...
Optimization arises naturally when process performance needs improvement. This is often the case in industry because of competition – the product has to be proposed at the lowest possible cost. From the point of view of control, optimization consists in de ...
Convex parameterization of fixed-order robust stabilizing controllers for systems with polytopic uncertainty is represented as an LMI using KYP Lemma. This parameterization is a convex inner-approximation of the whole non-convex set of stabilizing controll ...