This paper presents a novel control architecture system which is composed of a multi-objective cost function which Pareto optimises the programming of cutting parameters while adapting the milling process to new cutting conditions if new constraints appear. The paper combines a self-optimised module which looks for and finds Pareto optimal cutting parameters according to multi-objective purpose...

Capturing and storing the greenhouse gas carbon dioxide (CO2) produced by power plants could play a major role in minimizing climate change. In this study a postcombustion CO2 capture plant using MEA is designed, simulated, and optimized using the UniSim process simulator. The focus of this work is the subsequent optimal operation and control of the plant with the aim of staying close to the op...

This paper explores a vision of the design process in which components can optimize and verify themselves to improve efficiency, re-use, and confidence in correctness – the three design challenges identified by the International Technology Roadmap for Semiconductors. We illustrate what would take place for selfoptimization and self-verification before and after deployment of the design, and pre...

An adaptive filter is defined as a digital filter that has the capability of self adjusting its transfer function under the control of some optimizing algorithms. Most common optimizing algorithms are Least Mean Square (LMS) and Recursive Least Square (RLS). Although RLS algorithm perform superior to LMS algorithm, it has very high computational complexity so not useful in most of the practical...

Innovative self-optimizing systems which go far beyond current approaches for mechatronic products become possible when systems are enabled to optimize their own behavior at runtime. Such self-optimizing systems are characterized by their ability to endogenously modify their objectives in response to changing conditions and autonomously adapt their parameters and structure and as a result their...

Regions of control dependence identify the instructions in a program that execute under the same control conditions. They have a variety of applications in parallelizing and optimizing compilers. Two vertices in a control flow graph (which may represent instructions or basic blocks in a program) are in the same region if they have the same set of control dependence predecessors. The best known ...

The problem of cancellation of a nonstationary sinusoidal interference, acting at the output of an unknown multivariable linear stable plant, is considered. No reference signal is assumed to be available. The proposed feedback controller is a nontrivial extension of the SONIC (self-optimizing narrowband interference canceller) algorithm, developed earlier for single-input, single-output plants....

The algebraic Riccati equation plays the central role in the computation of the optimal control in the infinite time deterministic and stochastic linear regulator problem (Theorem 1). The problem of adaptive control of stochastic system combines the problems of identification and control of unknown system [3]. The most desirable solution of a stochastic adaptive control problem is to exhibit a ...

For the last 30 years, the microprocessor industry has relied on instruction-level par-allelism (ILP) and aggressive clock scaling to translate Moore's Law into exponential performance growth. Over this time frame, system performance has increased by a factor of 10, 000, enabling novel software applications and capabilities beyond the reach of earlier hardware platforms. Due to mounting challen...