Ahmed M. El-Garhy

Development of decoupling scheme for high order MIMO process based on PSO technique

Multiple-input multiple-output (MIMO) with N Input/ N Output processes are characterized by significant interactions between their inputs and outputs. The control of MIMO processes is usually implemented using sets of single-input single-output (SISO) loop controllers, which requires proper input–output pairing and development of decoupling compensator unit. In this paper, a generalized decoupling technique is proposed. The proposed technique uses relative gain array (RGA) to select proper pairing and particle swarm optimization (PSO) technique to estimate the optimal elements’ values of steady state decoupling compensation matrix constituting the decoupling compensator unit. The proposed technique is applied on 4 Input/ 4 Output two coupled distillation columns process, it proves remarkable success in minimizing the interaction between every input and all outputs except that output has been proper paired with.

Acoustic energy conversion into useful electric energy from Disk Jockey by using piezoelectric transducers

In this study a new noise source is proposed as a one of renewable energy sources in energy harvesting. Disk Jokey (DJ) is a common device in celebrations and other events. Converting the produced noise from DJ to electric energy by using a suitable piezoelectric transducer is the main aim of this study. Piezoelectric sensors are used to convert the sound waves to electric charges. Piezoelectric sensor of the model 7BB-41-2 is used in this study. The piezoelectric sensors are connected in series, parallel, and hybrid combination connections. The disk jockey is used as an acoustic noise source. The sound intensity levels of the output sound are 81, 84, 87 dB. The output of the three connection modes are measured at 0, 1,2,3,4, and 5cm distance. The results showed that the parallel connection gave the highest power at the various distances. The maximum generated power is 4.96m watts without using an external power supply for the signal condition device. The power decreases by increasing the distance from the source of the noise.

A New Hybrid BFOA-PSO Optimization Technique for Decoupling and Robust Control of Two-Coupled Distillation Column Process

The two-coupled distillation column process is a physically complicated system in many aspects. Specifically, the nested interrelationship between system inputs and outputs constitutes one of the significant challenges in system control design. Mostly, such a process is to be decoupled into several input/output pairings (loops), so that a single controller can be assigned for each loop. In the frame of this research, the Brain Emotional Learning Based Intelligent Controller (BELBIC) forms the control structure for each decoupled loop. The papers main objective is to develop a parameterization technique for decoupling and control schemes, which ensures robust control behavior. In this regard, the novel optimization technique Bacterial Swarm Optimization (BSO) is utilized for the minimization of summation of the integral time-weighted squared errors (ITSEs) for all control loops. This optimization technique constitutes a hybrid between two techniques, which are the Particle Swarm and Bacterial Foraging algorithms. According to the simulation results, this hybridized technique ensures low mathematical burdens and high decoupling and control accuracy. Moreover, the behavior analysis of the proposed BELBIC shows a remarkable improvement in the time domain behavior and robustness over the conventional PID controller.

A proposed technique for power extraction from acoustic energy scavenging

ABSTRACT In this study, converting acoustic to electric energy was achieved via the Disk Jockey (DJ) model TG5000, which worked as a noise source, and the piezoelectric model 7BB-41–2, which worked as a transducer. We proposed different states of piezoelectric transducer’s mounting on DJ and examined the results to determine the optimum state for maximization of the converted power. We proposed a technique which comprises four stages, and each stage is composed of a piezoelectric transducer followed by a voltage multiplier. The outputs of the four stages were connected in parallel, and these transducers were mounted via their bodies on the slim diaphragm of the acoustic focusing tube. The results indicated that the maximum converted power values were 1.225 mW with a load resistor of 10 kΩ for one stage, 1.089 mW with a load resistor of 10 kΩ for two stages, 1.682 mW with a load resistor of 5 kΩ for three stages, and 5.891mW with a load resistor of 2.2 kΩ for four stages at a sound intensity level of 85 dB and sound wave frequency of 2.1 kHz.

Novel Multi-input Multi-output Brain Emotional Learning Based Intelligent Controller for PUMA 560 Robotic Arm

A novel Multi-Input Multi-Output Brain Emotional Learning Based Intelligent Controller (MIMO-BELBIC) is introduced and applied as a controller of PUMA 560 robotic arm. PUMA 560 model is strongly coupled highly nonlinear model, which necessitate effective controller capable of dealing with high degree of coupling and nonlinearity. Furthermore, the robot is subjected to many sources of disturbances, which can affect the performance significantly. Mathematical model of MIMO-BELBIC is introduced and tailored to work as a controller of PUMA 560. Moreover, new optimization algorithm, designed especially for this problem, is used to optimize the 51 parameters of the controller. The results show remarkable success of the proposed controller in decreasing the tracking error (with/without) disturbances in comparison to the traditional PID controllers that were optimized by two different algorithms. Moreover, the proposed controller has minimal control effort with respect to the PID controllers.