What Is Intelligent Control? (with picture)

Geisha A. Legazpi

Intelligent control is the control method that mimics human intelligence when it comes to learning, decision-making, and problem solving. Human beings can experience, learn, adapt, and change their methods of approaching and solving problems. Computer engineers are looking for a way to recreate that natural intelligence with artificial intelligence. Practical applications for this control method are aimed toward a variety of fields that include computer technology, military applications, aeronautic applications, and robotics.

Though most contemporary military robots are remotely operated by a human, future combat drones may be able to adapt and respond to environments on their own.
Though most contemporary military robots are remotely operated by a human, future combat drones may be able to adapt and respond to environments on their own.

Although there are already many artificial intelligence approaches like neural networks, genetic algorithms, and Bayesian probability, the field of intelligent control is still developing and creating more control methods. Intelligent control is supported by computer science, mathematics, operations research, and control theory, while it also gets ideas from the life sciences. The most widely known control techniques, however, are neural networks and Bayesian probability.

Bayesian probability is also known as probability interpretations. This control method uses math algorithms to learn the issue and then apply the math to solve a problem. Neural networks use system identification and control theory to function. It is applied in speech recognition, image analysis, and adaptive control. Perhaps the most well-known application is the Xbox® Kinect™, a console game hardware that uses video and audio sensors to make users interact with a game by using their physical actions.

There is an increasing need for more advanced intelligent control in commercial, military, and industrial applications. Problems in these fields will always crop up, hence the need for self-organizing/learning control that can deal with these problems on their own. A good example of a practical application in intelligent control is unmanned aeronautical navigation, where unmanned aircraft learn to identify objects and to avoid them. The most sought after application for intelligent control in these fields is robotics and artificial intelligence.

The fields of robotics and artificial intelligence are more widely known for the application of intelligent control. Robots are pre-programmed with their own programming, thus scientists and researchers are looking for a more viable control method than what is currently available. The future of the field of robotics has already been explored in science fiction, but the present is still trying to get a working artificial intelligence that will not rely on pre-programmed instructions. A prime example of robotics and artificial intelligence that uses intelligent control is the child-robot with biomimetic body (CB2), an android that learns through its sensors and programming to function just like how a human child can develop. It also records emotional expressions and matches them with physical sensations.

You might also Like

Discuss this Article

Post your comments
Forgot password?