Past PID: Adaptive control is versatile, fast, accurate, report says

Microprocessors and advanced computing platforms have catalyzed the shift to adaptive controllers from proportional-integral-derivative (PID) controllers in process industries. Frost & Sullivan says adaptive control is gaining ground with improved performance in mechanical and nonmechanical systems. Links include....

04/08/2008


Palo Alto, CA – The advent of microprocessors and advanced computing platforms has catalyzed the shift to adaptive controllers from proportional-integral-derivative (PID) controllers in process industries. Continuous Adaptive Control – Technology Developments is a new analysis from Frost & Sullivan that reports adaptive control is being increasingly used because of its ability to improve performance in mechanical and nonmechanical systems.
In a Control Engineering article, “Techniques for Adaptive Control,” Vance VanDoren, consulting editor, says, “These latest control methodologies offer a means to revolutionize plant and process efficiency, response time, and profitability by allowing a process to be regulated by a form of rule-based artificial intelligence, without human intervention.” Also read “

Adaptive Controllers Work Smarter not Harder

” from Control Engineering .
Frost & Sullivan says adaptive controllers evolved from a solution for low-bandwidth applications to serve higher-bandwidth applications such as robots, spacecraft, and complex machining processes. Systems involving material, money, and supply and demand successfully incorporate adaptive controls. Missile control and guidance, fluid drive, industrial process control, power drag, firepower control system, ship navigation, and other nonlinear mechatronic systems now depend on this technology.
According to Frost & Sullivan research analyst S. Menaka, “While designing such complex and highly cognitive systems, developers need to be conscious of the time sensitivity of input and output data. Scientists will also have to consider other factors such as machine-human interface, ability to create cognitive solutions in a stipulated time, real-time performance control of the system, architecture independence, data normalization, and other such related factors.”
Due to time delays in operation or installation in systems with unknown dynamics, controllers were not traditionally used in mechanical systems. Following the advent of PID self-tuners, adaptive controllers became popular among commercial goods manufacturers and industry, Menaka says.
Offline training is imperative and scientists are compelled to consider the systems complexities. It was necessary that there be a trade-off among the error occurrences, correction identification, and steady performance of the system. Next-generation adaptive controllers use the model changes and the process output to compute the integrated square error (ISE) for each of three process parameters. After analysis of low, middle, and higher combinations of the parameters, 27 models can be devised, says Menaka.
“Through continued iterations, each model is normalized to a total ISE and the best value computed for each of the parameters is used in the next iteration as the middle value,” adds Menaka. “Thus, the model will undergo interpolation with re-centering of the parametric values to ultimately reach an optimum corrective model. As a high-end application, the control algorithm may also be embedded into an enterprise resource planning system. Eventually, scientists could develop a hybrid system comprising interacting subsystems.”
Future research will focus on other techniques, in addition to data analysis, inferential estimation, integration of neural network-based technologies into existing systems, and predictive control. There is a focus on developing new modeling methodologies; existing systems are under observation to integrate them with these. Emerging as an embedded technology, adaptive control will control higher-level functions. The control algorithm enhances the safety, economy, and reliability of the system and is responsible for its success or failure.
Continuous Adaptive Control– Technology Developments, part of the

Technical Insights subscription

, provides analysis of elements involved in the concept, PID controller, and tool path optimization software. It includes techniques of adaptive control such as model reference adaptive control, model free adaptive control, auto-tuning and self-tuning controllers, applications in domains, and trends. Technical Insights, an international technology analysis business, produces news alerts, newsletters, and research services.

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