Some about Control Engineering
Control engineering refers to a broad range of techniques and technologies which deals with the design, identification and analysis of systems with a view towards controlling them, i.e., to make them perform specific tasks or make them behave in a desired way. Multi-disciplinary in nature, control engineering activities seeks to understand physical systems using mathematical modeling in terms of inputs, outputs and various components with desired behavior; use control systems design tools to develope controllers for those systems; and implement controllers in physical systems employing available technology.
Originally, control engineering was all about contionuous, single-input/single-output systems in accordance to classical control theory. More recently, advancements in computer technology have allowed control engineers to overcome such limitations extending the framework to multiple-input/multiple output systems and moving to the discrete domain.
Advanced control schemes
With a broad expertise in control engineering, we at IDENER apply state-of-the-art control theory not just to tuning a predefined control scheme, but also to controller structure optimisation, system identification and implementation of advanced control systems, such as those listed next.
- Model predictive control: A class of control strategies based on the explicit use of a process model to generate the predicted values of the output at future time instants, which are then used to compute a sequence of control moves that optimize the future behavior of a plant.
- Neural networks: A series of algorithms that attempt to identify underlying relationships in a set of data by using a process that mimics the way the human brain operates. Neural networks have the ability to adapt to changing input so that the network produces the best possible result without the need to redesign the output criteria.
- Fuzzy logic: A mathematical logic that attemps to solve problems by assigning values to an imprecise spectrum of data in order to arrive at the most accurate conclusion possible. Fuzzy logic is designed to solve problems by considering all available information and making the best possible decision given the input.
- Adaptive control: A set of techniques which provide a systematic approach for automatic adjustment of controllers in real time, in order to achieve or to maintain a desured level of control system performance when the parameters of the plant dynamic model are unknown nad/or change in time.
- Robust control: A collection of powerful mathematical tools and efficient software algorithms able to guarantee some defined level of performance of the controlled system, irrespective of changes of plant dynamics.
