Optimal linear quadratic controller based on genetic algorithm for TCP/AQM router

Evaporation from surface water plays a crucial role in water accounting of basins, water resource management, and irrigation systems management. As such, the simulation of evaporation with high accuracy is very important. In this study, two methods for simulating pan evaporation under different climatic conditions in Iran were developed. In the first method, six experimental relationships (linear, quadratic, and cubic, with two input combinations) were determined for Iran’s six climate types, inspired by a multilayer perceptron neural network (MLP-NN) neuron and optimized with the genetic algorithm. The best relationship of the six was selected for each climate type, and the results were presented in a three-dimensional graph. The best overall relationship obtained in the first method was used as the basic relationship in the second method, and climatic correction coefficients were determined for other climate types using the genetic algorithm optimization model. Finally, the accuracy of the two methods was validated using data from 32 synoptic weather stations throughout Iran. For the first method, error tolerance diagrams and statistical coefficients showed that a quadratic experimental relationship performed best under all climatic conditions. To simplify the method, two graphs were created based on the quadratic relationship for the different climate types, with the axes of the graphs showing relative humidity and temperature, and with pan evaporation, were drawn as contours. For the second method, the quadratic relationship for semi-dry conditions was selected as the basic relationship. The estimated climatic correction coefficients for other climate types lay between 0.8 and 1 for dry, semi-dry, semi-humid, Mediterranean climates, and between 0.4 and 0.6 for humid and very humid climates, indicating that one single relationship cannot be used to simulate pan evaporation for all climatic conditions in Iran. The validation results confirmed the accuracy of the two methods in simulating pan evaporation under different climatic conditions in Iran.

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Optimal linear quadratic control for wireless sensor and actuator networks with random delays and packet dropouts

International Journal of Distributed Sensor Networks ◽

10.1177/1550147718779560 ◽

2018 ◽

Vol 14 (6) ◽

pp. 155014771877956

Author(s):

Zhuwei Wang ◽

Lihan Liu ◽

Chao Fang ◽

Xiaodong Wang ◽

Pengbo Si ◽

...

Keyword(s):

Frequency Control ◽

Optimal Solution ◽

Load Frequency Control ◽

Wireless Sensor ◽

Linear Quadratic Control ◽

Linear Quadratic ◽

Relay Nodes ◽

Packet Dropouts ◽

Frequency Control System ◽

Optimal Linear

In this article, the optimal linear quadratic control problem is considered for the wireless sensor and actuator network with stochastic network-induced delays and packet dropouts. Considering the event-driven relay nodes, the optimal solution is obtained, which is a function of the current plant state and all past control signals. It is shown that the optimal control law is the same for all locations of the controller placement. Since the perfect plant state information is available at the sensor, the optimal controller should be collocated with the sensor. In addition, some issues such as the plant state noise and suboptimal solution are also discussed. The performance of the proposed scheme is investigated by an application of the load frequency control system in power grid.

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Approximate solution to optimal linear quadratic Gaussian control over non-acknowledgment networks

Journal of the Franklin Institute ◽

10.1016/j.jfranklin.2019.11.046 ◽

2020 ◽

Vol 357 (4) ◽

pp. 2049-2066

Author(s):

Hong Lin ◽

Mei Liu ◽

Huaicheng Yan ◽

Jinliang Liu ◽

Shan Lu

Keyword(s):

Approximate Solution ◽

Linear Quadratic ◽

Linear Quadratic Gaussian ◽

Optimal Linear

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An LQG Controller Based on Real System Identification for an Active Hydraulically Interconnected Suspension

Mathematical Problems in Engineering ◽

10.1155/2020/6669283 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Yaohua Guo ◽

Bin Wang ◽

Anton Tkachev ◽

Nong Zhang

Keyword(s):

Transfer Function ◽

Physical Model ◽

Hidden Variables ◽

Roll Angle ◽

Ball Screw ◽

Vehicle Body ◽

Linear Quadratic ◽

Rollover Prevention ◽

Body Roll ◽

Optimal Linear

Rollover prevention is always one of the research hotspots in vehicle design. Active hydraulically interconnected suspension (HIS) is a promising technology to reduce vehicle body roll angle caused by different driving inputs and road conditions. This paper proposes a novel actuator of the active HIS system. The actuator consists of two cylinders, a ball screw, and only one motor. The actuator proposed can reduce the number of motors needed in the system. Meanwhile, forced vibration identification (FVI) is used to identify the transfer function of a half-car physical model and a Kalman state observer is applied to eliminate the influence of sensor noise. The FVI method can eliminate most model uncertainties and hidden variables. Aggressive and moderate optimal linear quadratic Gaussian (LQG) methods are implemented to control the motion of the vehicle body based on the identified transfer function of the physical model. The performance of an active HIS system with an aggressive and moderate LQG controller is compared with that of a passive HIS system. The effectiveness of the LQG controller is validated by simulation and experimental results. Also, the obtained results show that the stabilization speed of the active HIS system is 20% faster than that of the passive HIS system and the roll angle can be reduced up to 55% than that of the passive HIS system.

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Modeling and Speed Tuning of a PMSM with Presence of Fissure Using Dragonfly Algorithm

Applied Sciences ◽

10.3390/app10248823 ◽

2020 ◽

Vol 10 (24) ◽

pp. 8823

Author(s):

Omar Aguilar-Mejía ◽

Abraham Manilla-García ◽

Ivan Rivas-Cambero ◽

Hertwin Minor-Popocatl

Keyword(s):

Control Method ◽

Fault Tolerant ◽

Permanent Magnet Synchronous Motor ◽

Linear Quadratic Control ◽

Linear Quadratic ◽

Search Range ◽

Trajectory Tracking Control ◽

Dragonfly Algorithm ◽

Optimal Linear ◽

Motor Operation

This paper presents a robust trajectory tracking control for a Permanent Magnet Synchronous Motor (PMSM) with consideration a fault, parametric uncertainties and external disturbances by effectively integrating robust optimal linear quadratic control. One kind of fault is considered in the machine, particularly the presence of fissure rotor. The dynamic model of the PMSM with the presence of fissure presents highly non-linear behaviors, which means that tuning is quite complicated, which the tuning was chosen through swarm intelligence optimization (Dragonfly Algorithm). A sensitivity analysis is carried out, in order to limit the search range to minimize the evaluation time. This methodology was used to diminish these defects during motor operation. Simulation results show that the optimal linear quadratic control method has a robust fault-tolerant performance.

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A genetic algorithm–based design approach for smart base isolation systems

Journal of Intelligent Material Systems and Structures ◽

10.1177/1045389x17733058 ◽

2017 ◽

Vol 29 (7) ◽

pp. 1315-1332 ◽

Cited By ~ 3

Author(s):

Mohtasham Mohebbi ◽

Hamed Dadkhah ◽

Hamed Rasouli Dabbagh

Keyword(s):

Genetic Algorithm ◽

Optimization Problem ◽

Base Isolation ◽

Design Procedure ◽

Design Parameters ◽

Linear Quadratic ◽

Isolation System ◽

Isolation Systems ◽

Magneto Rheological ◽

Smart Base Isolation

This article presents a new approach for designing effective smart base isolation systems composed of a low-damping linear base isolation and a semi-active magneto-rheological damper. The method is based on transforming the design procedure of the hybrid base isolation system into a constrained optimization problem. The magneto-rheological damper command voltages have been determined using H2/linear quadratic Gaussian and clipped-optimal control algorithms. Through a sensitivity analysis to identify the effective design parameters, base isolation and control algorithm parameters have been taken as design variables and optimally determined using genetic algorithm. To restrict increases in floor accelerations, the objective function of the optimization problem has been defined as minimizing the maximum base drift while putting specific constraint on the acceleration response. For illustration, the proposed method has been applied to design a semi-active hybrid isolation system for a four-story shear building under earthquake excitation. The results of numerical simulations show the effectiveness, simplicity, and capability of the proposed method. Furthermore, it has been shown that using the proposed method, the acceleration of the isolated structure can also be incorporated into design process and practically controlled with a slight sacrifice of control effectiveness in reducing the base drift.

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Optimal linear quadratic guidance law with terminal impact angle constraint

2017 29th Chinese Control And Decision Conference (CCDC) ◽

10.1109/ccdc.2017.7978462 ◽

2017 ◽

Author(s):

Zhao Jianyu ◽

Yu Jianqiao ◽

Yang Kun

Keyword(s):

Impact Angle ◽

Linear Quadratic ◽

Guidance Law ◽

Optimal Linear ◽

Impact Angle Constraint

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A novel optimal configuration of sensor and actuator using a non-linear integer programming genetic algorithm for active vibration control

Journal of Intelligent Material Systems and Structures ◽

10.1177/1045389x16685439 ◽

2017 ◽

Vol 28 (15) ◽

pp. 2074-2081 ◽

Cited By ~ 9

Author(s):

Chunyou Zhang ◽

Lihua Wang ◽

Xiaoqiang Wu ◽

Weijin Gao

Keyword(s):

Genetic Algorithm ◽

Integer Programming ◽

Vibration Control ◽

Active Vibration Control ◽

Flexible Structures ◽

Linear Quadratic ◽

Linear Integer Programming ◽

Optimal Criterion ◽

Non Linear ◽

Active Vibration

Due to widespread applications of a large number of flexible structures, to obtain the best dynamic control performance of a system, optimal locations of the actuators and sensors are necessary to be determined. This article proposes a novel optimal criterion for the actuators or sensors ensuring good controllability or observability of a structure, and also considering the remaining modes to control the spillover effect. Based on the proposed optimization criteria, a non-linear integer programming genetic algorithm is employed to achieve the optimal configurations. Active vibration control is investigated for a cantilever plate with the actuators in optimal positions to suppress the specified modes utilizing linear quadratic regulator controller. Several simulation results validate the efficiency and feasibility of the proposed optimal criteria.

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