scholarly journals Self-Learning Salp Swarm Optimization Based PID Design of Doha RO Plant

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 287
Author(s):  
Naresh Patnana ◽  
Swapnajit Pattnaik ◽  
Tarun Varshney ◽  
Vinay Pratap Singh
Keyword(s):  
Reverse Osmosis ◽  
State Of The Art ◽  
Pid Controllers ◽  
Test Cases ◽  
Proportional Integral Derivative ◽  
Swarm Optimization ◽  
System A ◽  
Reverse Osmosis Plant ◽  
The Time Domain ◽  
Self Learning

In this investigation, self-learning salp swarm optimization (SLSSO) based proportional- integral-derivative (PID) controllers are proposed for a Doha reverse osmosis desalination plant. Since the Doha reverse osmosis plant (DROP) is interacting with a two-input-two-output (TITO) system, a decoupler is designed to nullify the interaction dynamics. Once the decoupler is designed properly, two PID controllers are tuned for two non-interacting loops by minimizing the integral-square-error (ISE). The ISEs for two loops are obtained in terms of alpha and beta parameters to simplify the simulation. Thus designed ISEs are minimized using SLSSO algorithm. In order to show the effectiveness of the proposed algorithm, the controller tuning is also accomplished using some state-of-the-art algorithms. Further, statistical analysis is presented to prove the effectiveness of SLSSO. In addition, the time domain specifications are presented for different test cases. The step responses are also shown for fixed and variable reference inputs for two loops. The quantitative and qualitative results presented show the effectiveness of SLSSO for the DROP system.

Auto PID Tuning of Speed Control of DC Motor Using Particle Swarm Optimization Based on FPGA

2015 ◽  
Vol 776 ◽  
pp. 390-395 ◽  
Author(s):  
Hilal Tayara ◽  
Deok Jin Lee ◽  
Kil To Chong
Keyword(s):  
Particle Swarm Optimization ◽  
Steady State ◽  
Rise Time ◽  
Particle Swarm ◽  
Speed Control ◽  
Dc Motor ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Swarm Optimization ◽  
Pid Tuning

This paper introduces auto tuning of proportional-integral-derivative (PID) controllers of DC motor using particle swarm optimization (PSO) method. The DC motor was modeled in Simulink and PSO was implanted on FPGA “cyclone IV E” using the soft processor NIOS II. The results were efficient in reducing the steady state error, settling time, rise time and maximum overshoot in speed control of a DC motor.

scholarly journals Solving Cold-Standby Reliability-Redundancy Allocation Problems with Particle-Based Simplified Swarm Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Chia-Ling Huang ◽  
Yunzhi Jiang ◽  
Wei-Chang Yeh
Keyword(s):  
Particle Swarm Optimization ◽  
System Reliability ◽  
State Of The Art ◽  
Series System ◽  
Swarm Optimization ◽  
Redundancy Allocation ◽  
System A ◽  
Cold Standby ◽  
Allocation Problems ◽  
Intelligence Technique

Particle swarm optimization (PSO) and simplified swarm optimization (SSO) are two of the state-of-the-art swarm intelligence technique that is widely utilized for optimization purposes. This paper describes a particle-based simplified swarm optimization (PSSO) procedure which combines the update mechanisms (UMs) of PSO and SSO to determine optimal system reliability for reliability-redundancy allocation problems (RRAPs) with cold-standby strategy while aimed at maximizing the system reliability. With comprehensive experimental test on the typical and famous four benchmarks of RRAP, PSSO is compared with other recently introduced algorithms in four different widely used systems, i.e., a series system, a series-parallel system, a complex (bridge) system, and an overspeed protection system for a gas turbine. Finally, the results of the experiments demonstrate that the PSSO can effectively solve the system of RRAP with cold-standby strategy and has good performance in the system reliability obtained although the best system reliability is not obtained in all four benchmarks.

scholarly journals Analysis of the Practical Implementation of Flicker Measurement Coprocessor for AMI Meters

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1589
Author(s):  
Krzysztof Kołek ◽  
Andrzej Firlit ◽  
Krzysztof Piątek ◽  
Krzysztof Chmielowiec
Keyword(s):  
Code Generation ◽  
State Of The Art ◽  
Power Grids ◽  
Practical Implementation ◽  
System A ◽  
Measuring Devices ◽  
Point Representation ◽  
Measurement Algorithm ◽  
On Chip ◽  
Vhdl Code

Monitoring power quality (PQ) indicators is an important part of modern power grids’ maintenance. Among different PQ indicators, flicker severity coefficients Pst and Plt are measures of voltage fluctuations. In state-of-the-art PQ measuring devices, the flicker measurement channel is usually implemented as a dedicated processor subsystem. Implementation of the IEC 61000-4-15 compliant flicker measurement algorithm requires a significant amount of computational power. In typical PQ analysers, the flicker measurement is usually implemented as a part of the meter’s algorithm performed by the main processor. This paper considers the implementation of the flicker measurement as an FPGA module to offload the processor subsystem or operate as an IP core in FPGA-based system-on-chip units. The measurement algorithm is developed and validated as a Simulink diagram, which is then converted to a fixed-point representation. Parts of the diagram are applied for automatic VHDL code generation, and the classifier block is implemented as a local soft-processor system. A simple eight-bit processor operates within the flicker measurement coprocessor and performs statistical operations. Finally, an IP module is created that can be considered as a flicker coprocessor module. When using the coprocessor, the main processor’s only role is to trigger the coprocessor and read the results, while the coprocessor independently calculates the flicker coefficients.

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