In dynamic systems, it is very difficult to have models with good accuracy that are sufficient to predict the plant behavior in a way that an acceptably controlled performance can be produced. Sometimes even if mathematical models are sufficiently accurate in a way that a good controlled performance can be obtained, long term operation (or even short term in some cases) gradually increases the difference between the plant and its dynamical model. That, in turn, would lead to a degraded performance. It is a common task in industrial applications to recalibrate the control system periodically, as the plant parameters suffer various fluctuations from their original values that were used in designing the control system. The calibration procedure usually requires professional attendance, which adds up to more maintenance costs. Also, the experimental nature of the manual calibration often requires at least part of the plant operations to be halted. Adapted from MRAC framework using PID and fuzzy controller, a modified climbing algorithm was introduced in order to compensate the signal. This simulation was applied in fixed-wing airplane pitch angle in Simulink MATLAB. The result demonstrated that effectiveness of the proposed tuning algorithm and improvement over the initial non-tuned response of the process.
Poly(vinyl chloride) photodecomposition films that contains melamine Schiff base (0.5% by weight) as photostabilizers upon preservation with an ultraviolet light (UV) was investigated. The photodecomposition rate constant was reduced significantly in existence of melamine Schiff base compared to PVC (blank). The Schiff base 1 was found to most effective additive in PVC photostabilization films. Photodecomposition rate content for PVC films containing Schiff base 1 was found to be 5 × 10-3 sec-1 compared to 8.7 × 10-3 sec-1 for blank film. Ultraviolet radiation aging behaviors of PVC films were studied through leaching test by measuring the degree of migration. The surface morphology of PVC films was inspected by scanning electron microscope.
Quantum-dot Cellular Automata (QCA) is a new emerging nano-electronic technology. Owing to its many favorable features, such as low energy requirements, high speed, and small size, QCA is being actively suggested as a future CMOS replacement by researchers. Many digital circuits have been introduced in QCA technology, most of them aiming to reach the function with optimum construction in terms of area, cell count and power consumption. The memory circuit is the main building block in the digital system therefore the researchers paid attention to design the memory cells with minimum requirements. In this paper, a new methodology is introduced to design two forms of CAM cells. The proposed designs required two 2:1 multiplexers, one OR gate and one inverter. The first proposed design reduces the power consumption by 53.3%, 35% and 25.9% at (0.5 Ek, 1 Ek, and 1.5 Ek) while the second design by 53.2%, 31.9% and 20.5% (0.5 Ek, 1 Ek, and 1.5 Ek) respectively.
In this paper, the PID and fuzzy logic controllers are designed to control the pitch and yaw angles of a twin rotor MIMO system (TRMS) in simulation-based platform. Two controllers were used in each case, one for pitch angle and one for yaw angle. The twin rotor MIMO system designed as decoupling system in simplification. The tuned controllers gave a very good response in the simulation. These results will provide a solid base for designing the final optimized real-time controller in the next stages of the research.
In this chapter, an intelligent algorithmic tuning technique suitable for real-time system tuning based on hill climbing optimization algorithm and model reference adaptive control (MRAC) system technique is proposed. Although many adaptive control tuning methodologies depend partially or completely on online plant system identification, the proposed method uses only the model that is used to design the original controller, leading to simplified calculations that do not require neither high processing power nor long processing time, as opposed to identification technique calculations. Additionally, a modified hill climbing algorithm that is developed in this research is specifically designed, configured and tailored for the automatic tuning of control systems. The modified hill climbing algorithm uses a systematic movement when searching for new solution candidates. The algorithm measures the quality of the solution candidate based on error function. The error function is generated by comparing the system response with a desired reference response. The algorithm tests new solution candidates using step signals iteratively. The results showed the algorithm effectiveness to drive the system response. The simulation results illustrate that the method schemes proposed in this study show a viable and versatile solution to deal with controller tuning for systems with model inaccuracies as well as controller real-time calibration problem.
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