A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Samuel, S. Prince
- Adaptive Temperature Control System for LED Array Systems
Authors
Source
Fuzzy Systems, Vol 8, No 5 (2016), Pagination: 148-153Abstract
In this paper, an adaptive temperature control system for plant cultivation is proposed.The proposed method analyses the internal temperature of red and blue LED arrays and determines the optimal fan speed for various temperature conditions. The adaptive control system is then implemented based on the analysed data. Hence, the proposed system can better reduce the fan control power and noise than the conventional method. In the experimental results, the error between the simulation model and real system was at most 2.96%. The proposed method reduced the power consumption to 60% that of the conventional system when the target temperature was 38 °C.
Keywords
Light Emitting Diode, Temperature Control, Power Reduction
- Real Time Implementation of Enhanced Nonlinear PID Controller for a Conical Tank Process
Authors
Source
Data Mining and Knowledge Engineering, Vol 8, No 6 (2016), Pagination: 188-192Abstract
Level is one of the most important parameter that has to be monitored and controlled in any process industry. Conical tanks are widely used in many industries due to its shape which provides easy discharge of water when compared to other tanks. Moreover, liquid level control of a conical tank is still challenging for typical process control because of nonlinearities. Since PID control is the workhorse of almost 90% of the industries, an Enhanced Nonlinear PID (EN-PID) controller is proposed which exhibits the improved performance than the conventional linear fixed-gain PID controller, by incorporating a sector-bounded nonlinear gain in cascade with a conventional PID control architecture. To achieve the high robustness against noise, two nonlinear tracking differentiators are proposed to select high-quality differential signal in the presence of measurement noise. The main advantages of the proposed EN-PID controller lie in its high robustness against noise and ease of implementation. And in the proposed technique a EN-PID is designed and tuned using the Bee colony optimization (BCO) technique. The BCO algorithm is based on the model that is obtained from the communicative behavior of the honey bees. Simulation results performed on a conical tank level process are presented to demonstrate the performance of the developed EN-PID controller.