Design of a fuzzy-PID controller for a nonlinear hydraulic turbine governing system by using a novel gravitational search algorithm based on Cauchy mutation and mass weighting

High Net Information Density DNA Data Storage by the MOPE Encoding Algorithm

DNA has recently been recognized as an attractive storage medium due to its high reliability, capacity, and durability. However, encoding algorithms that simply map binary data to DNA sequences have the disadvantages of low net information density and high synthesis cost. Therefore, this paper proposes an efficient, feasible, and highly robust encoding algorithm called MOPE (Modified Barnacles Mating Optimizer and Payload Encoding). The Modified Barnacles Mating Optimizer (MBMO) algorithm is used to construct the non-payload coding set, and the Payload Encoding (PE) algorithm is used to encode the payload. The results show that the lower bound of the non-payload coding set constructed by the MBMO algorithm is 3%-18% higher than the optimal result of previous work, and theoretical analysis shows that the designed PE algorithm has a net information density of 1.90 bits/nt, which is close to the ideal information capacity of 2 bits per nucleotide. The proposed MOPE encoding algorithm with high net information density and satisfying constraints can not only effectively reduce the cost of DNA synthesis and sequencing but also reduce the occurrence of errors during DNA storage.

A Pitch Angle Controller Based on Novel Fuzzy-PI Control for Wind Turbine Load Reduction

A novel fuzzy rule is proposed to adopt a positive pitch strategy when the error between the measured and rated generator speed becomes large and continues to increase, and to adopt a negative pitch strategy when the error is small. The improved approach is introduced into the normal Fuzzy-Proportional-Integral (Fuzzy-PI) control strategy by dividing the fuzzy rules into four areas and analyzing the design method for each area. Furthermore, a low pass filter is used to reduce the ultimate loads of the pitch driver caused by the novel fuzzy rules. The modeling of the wind turbine load under turbulent wind conditions is conducted in GH Bladed, and MATLAB/Simulink is used to interact with the modeling to verify the novel Fuzzy-PI control. The results show that, compared with normal Fuzzy-PI control, the novel Fuzzy-PI control can greatly reduce the ultimate loads and fatigue loads of the pitch driver. The novel Fuzzy-PI control not only reduces the extremum of power deviation, but also decreases some ultimate loads and fatigue loads of the tower base and the blade root. It can reduce these loads by up to 21.53% under the normal turbulent wind condition and by up to 18.14% under the extreme turbulent wind condition.

Fuzzy Multi-Regional Fractional PID controller for Pressurized Water nuclear Reactor

The paper presents the methodology for the synthesis of a Fuzzy Multi-Regional Fractional Order PID controller (FMR-FOPID) used to control the average thermal power of a PWR nuclear reactor in the load following mode. The controller utilizes a set of FOPID controllers and the fuzzy logic Takagi-Sugeno reasoning system. The proposed methodology is based on two optimization parts. The first part is devoted to finding the optimal parameters of local FOPID controllers and in the second part, the optimal membership functions of the fuzzy reasoning system are designed. During the controller designing and comparison phase, the two validated nodal models of a nuclear reactor are used, simplified model and extended model respectively. The proposed approach has been verified by computer simulations that confirm its effectiveness.

Proportional–Integral–Derivative Controller Design Using an Advanced Lévy-Flight Salp Swarm Algorithm for Hydraulic Systems

To improve the control ability of proportional–integral–derivative (PID) controllers and increase the stability of force actuator systems, this paper introduces a PID controller based on the self-growing lévy-flight salp swarm algorithm (SG-LSSA) in the force actuator system. First, the force actuator system model was built, and the transfer function model was obtained by the identification of system parameters identifying. Second, the SG-LSSA was proposed and used to test ten benchmark functions. Then, SG-LSSA-PID, whose parameters were tuned by SG-LSSA, was applied to the electro-hydraulic force actuator system to suppress interference signals. Finally, the temporal response characteristic and the frequency response characteristic were studied and compared with different algorithms. Ten benchmark function experiments indicate that SG-LSSA has a superior convergence speed and perfect optimization capability. The system performance results demonstrate that the electro-hydraulic force actuator system utilized the SG-LSSA-PID controller has a remarkable capability to maintain the stability and robustness under unknown interference signals.

Characteristics Analysis and Fuzzy Fractional-Order PID Parameter Optimization for Primary Frequency Modulation of a Pumped Storage Unit Based on a Multi-Objective Gravitational Search Algorithm

Compared with conventional hydropower units, the pumped storage unit has the characteristics of diverse working conditions and frequent switching. Therefore, the stability and regulation quality of the primary frequency modulation transition process of the regulating system is very important. Due to the “S” characteristics of the pumped storage unit (PSU), the pumped storage unit regulating system has a strong nonlinearity, and the conventional proportional-integral-derivative (PID) controller cannot provide high-quality control under low water head conditions. In this paper, the nonlinear PSU model with an elastic water hammer effect is studied, and the fuzzy fractional-order PID (FFOPID) controller is designed to improve the stability of the system. The membership function and the control parameters of the fractional-order PID are optimized based on the multi-objective gravitational search algorithm (MOGSA). The experimental results show that the optimized design of the FFOPID controller has better control quality than the traditional PID controller, the fractional-order PID (FOPID) controller, and the fuzzy PID controller (FPID) when the system is disturbed by the rotating speed under low water head.

Impact of Tail Water Fluctuation on Turbine Start-Up and Optimized Regulation

Small hydropower plants are usually run-of-river with a poor adjustment capacity, and, therefore, large tail water fluctuation may be induced during flood discharge. Meanwhile, the turbine units need to be quickly started-up due to the regulation requirements of the power grid. However, failures of the start-up and grid connection are often encountered because of severe tail water fluctuation. In order to achieve the rapid and stable start-up under tail water fluctuations and to reduce the negative effect of start-up on turbine runner blades, the fluctuation law of the tail water from flood discharge model test is introduced as the boundary condition. A multi-objective comprehensive (MOC) index is proposed to optimize the parameters of the governor. Then the impacts of the tail water amplitude and frequency on the start-up are simulated and analyzed. Moreover, the start-up characteristics under the Integral Time Absolute Error (ITAE) index and the MOC index are compared through particle swarm optimization (PSO). The results show that both indices can ensure the rapidity of start-up under tail water fluctuation, whereas the MOC index can achieve a more stable start-up process. Therefore, the MOC index has a better stability and a less negative effect on the turbine runner blades.

A Mixed-Strategy-Based Whale Optimization Algorithm for Parameter Identification of Hydraulic Turbine Governing Systems with a Delayed Water Hammer Effect

For solving the parameter optimization problem of a hydraulic turbine governing system (HTGS) with a delayed water hammer (DWH) effect, a Mixed-Strategy-based Whale Optimization Algorithm (MSWOA) is proposed in this paper, in which three improved strategies are designed and integrated to promote the optimization ability. Firstly, the movement strategies of WOA have been improved to balance the exploration and exploitation. In the improved movement strategies, a dynamic ratio based on improved JAYA algorithm is applied on the strategy of searching for prey and a chaotic dynamic weight is designed for improving the strategies of bubble-net attacking and encircling prey. Secondly, a guidance of the elite’s memory inspired by Particle swarm optimization (PSO) is proposed to lead the movement of the population to accelerate the convergence speed. Thirdly, the mutation strategy based on the sinusoidal chaotic map is employed to avoid prematurity and local optimum points. The proposed MSWOA are compared with six popular meta-heuristic optimization algorithms on 23 benchmark functions in numerical experiments and the results show that the MSWOA has achieved significantly better performance than others. Finally, the MSWOA is applied on parameter identification problem of HTGS with a DWH effect, and the comparative results confirm the effectiveness and identification accuracy of the proposed method.

A Real-Time Accurate Model and Its Predictive Fuzzy PID Controller for Pumped Storage Unit via Error Compensation

Model simulation and control of pumped storage unit (PSU) are essential to improve the dynamic quality of power station. Only under the premise of the PSU models reflecting the actual transient process, the novel control method can be properly applied in the engineering. The contributions of this paper are that (1) a real-time accurate equivalent circuit model (RAECM) of PSU via error compensation is proposed to reconcile the conflict between real-time online simulation and accuracy under various operating conditions, and (2) an adaptive predicted fuzzy PID controller (APFPID) based on RAECM is put forward to overcome the instability of conventional control under no-load conditions with low water head. Respectively, all hydraulic factors in pipeline system are fully considered based on equivalent lumped-circuits theorem. The pretreatment, which consists of improved Suter-transformation and BP neural network, and online simulation method featured by two iterative loops are synthetically proposed to improve the solving accuracy of the pump-turbine. Moreover, the modified formulas for compensating error are derived with variable-spatial discretization to improve the accuracy of the real-time simulation further. The implicit RadauIIA method is verified to be more suitable for PSUGS owing to wider stable domain. Then, APFPID controller is constructed based on the integration of fuzzy PID and the model predictive control. Rolling prediction by RAECM is proposed to replace rolling optimization with its computational speed guaranteed. Finally, the simulation and on-site measurements are compared to prove trustworthy of RAECM under various running conditions. Comparative experiments also indicate that APFPID controller outperforms other controllers in most cases, especially low water head conditions. Satisfying results of RAECM have been achieved in engineering and it provides a novel model reference for PSUGS.