CN117170250B - Water conservancy monitoring equipment control optimization method based on meta heuristic algorithm - Google Patents
Water conservancy monitoring equipment control optimization method based on meta heuristic algorithm Download PDFInfo
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 134
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Abstract
The invention discloses a water conservancy monitoring equipment control optimization method based on a meta heuristic algorithm, which belongs to the field of PID control of water conservancy monitoring equipment and comprises the following specific steps: step one, determining a target monitoring range and monitoring precision of water quality by water conservancy monitoring equipment; step two, converting the control problem of the water conservancy monitoring equipment into a meta heuristic algorithm optimization problem, and establishing an optimized structure model and a simulation model to be optimized by adopting a PID control strategy in water conservancy monitoring control; aiming at the disturbance requirements of water conservancy monitoring equipment, improving a meta heuristic algorithm; optimizing the hydraulic monitoring PID control parameters by using an improved meta heuristic algorithm; step five, according to real-time feedback information of the water conservancy monitoring equipment, the algorithm automatically adjusts PID control parameters, so that the system output is as close to the target monitoring precision and range as possible, and the water conservancy equipment is accurately controlled; the problem that water conservancy monitoring equipment control is easily disturbed by the environment is solved.
Description
Technical Field
The invention relates to the field of PID control of water conservancy monitoring equipment, in particular to a water conservancy monitoring equipment control optimization method based on a meta heuristic algorithm.
Background
In water resource detection control, PID (proportional-integral-derivative) control is a common control strategy, in sewage treatment and water purification systems, water resource parameters such as PH value or oxidation-reduction potential need to be controlled, a PID controller can generate a control signal to adjust the opening of an administration device or an electric valve by comparing a signal sent by a measuring sensor with expected water conservancy, so as to change the dosage of the administered medicament or change the water flow path, and further control the quality of the water resource; in many water treatment facilities, it is also desirable to maintain the level of the pool or tank at a particular level, and the PID controller can vary the level of the liquid level by measuring the level and comparing it to a desired level to generate a control signal to adjust the opening of the pump or valve. In these application scenarios, the PID controller adjusts the input signal of the system by continuously comparing the actual measured value with the desired value, so that the output of the system is as close to the desired value as possible; the PID controller is simple, easy to realize and high in reliability, so that the PID controller is widely applied to a plurality of water treatment and water supply systems; however, it should be noted that other factors, such as nonlinearity, time-varying property, disturbance, etc., of the system need to be considered in practical application, and more complex control strategies need to be adopted to improve control accuracy and robustness. The fire hawk optimization algorithm (FHO) is a new meta-heuristic algorithm, and is used for solving an optimization problem based on the foraging behavior of fire hawks in the nature; specifically, the process of capturing prey by fire hawk is simulated, and the optimal solution is found through actions such as igniting, transmitting fire and capturing prey.
Disclosure of Invention
The invention aims at: the control optimizing method for the water conservancy monitoring equipment is provided, PID is optimized by using an improved meta heuristic algorithm, and the performance of PID control, which is easily affected by disturbance, is improved under a complex water conservancy environment, so that the precision of the water conservancy monitoring equipment is improved in the aspect of water conservancy, and the water resource parameters are reasonably and accurately controlled.
In order to achieve the purpose, the invention adopts the following technical scheme that the water conservancy monitoring equipment control optimization method based on the meta heuristic algorithm comprises the following specific steps:
step one, determining a target monitoring range and monitoring precision of water resources by water conservancy monitoring equipment;
step two, converting the control problem of the water conservancy monitoring equipment into a meta heuristic algorithm optimization problem, and establishing an optimized structure model and a simulation model to be optimized by adopting a PID control strategy in water conservancy monitoring control;
aiming at the disturbance requirement of water conservancy monitoring equipment, improving a fire hawk optimization algorithm, wherein the improvement comprises two parts;
d1, introducing nonlinear disturbance factors into a hunting position updating strategy of a fire hawk optimization algorithmThe formula is:
；
in the method, in the process of the invention,the number of bits in the space is searched for the algorithm,the current iteration number;
and D2, fusing the pelican optimization algorithm in the exploration phase of the fire hawk optimization algorithm, and introducing an optimal position strategy, wherein a position updating strategy formula of the improved fire hawk optimization algorithm in the exploration phase is as follows:
（1）；
in the method, in the process of the invention,is the firstOnly the new location of the fire hawk,is the firstOnly the position of the last iteration of the fire hawk,is [0,1]Random numbers in the range of the random numbers,for the optimal position of the current iteration,is a random integer of 1 or 2,is the firstThe prey quilt is the firstNew locations surrounded by fire hawks;
step four, optimizing PID control parameters of the water conservancy monitoring equipment by utilizing an improved fire hawk optimization algorithm to obtain optimal PID control parameters;
and fifthly, applying the optimizing optimal parameters to the water conservancy monitoring equipment, and automatically adjusting PID control parameters by an algorithm according to real-time feedback information of the water conservancy monitoring equipment, so that the system output reaches the target monitoring precision and range, and the water conservancy equipment is accurately controlled.
Further, the first step, the water conservancy monitoring device is mainly used for monitoring hydrologic water conservancy data, the water conservancy monitoring device can realize the omnibearing monitoring of water resources, timely and accurate data support is provided for water resource management, and a target monitoring range and monitoring accuracy are determined so as to accurately control the water resource environment.
Furthermore, in the second step, the control problem of the water conservancy monitoring device is usually controlled by using a PID control mode, and the structural model and the simulation model mainly comprise a control system target value input module, a control system monitoring and measuring module, an error value module, a PID controller module, an improved fire hawk optimization algorithm module and a controlled object module; the control system target value input module is mainly used for inputting a target monitoring value of the water resource by the water conservancy monitoring equipment, the control system monitoring and measuring module is used for collecting a real-time value of the water resource monitoring by the water conservancy monitoring equipment, and the controlled object module is mainly used for adjusting the water conservancy monitoring equipment.
Further, the steps ofStep three, introducing nonlinear disturbance factorsThe disturbance factor is as followsIs a nonlinear disturbance of the center, along withAnd (3) withThe distance of the non-linear disturbance factor increases, the disturbance intensity gradually decreases, and the search space median of the non-linear disturbance factorThe value is 0.5, the nonlinear disturbance factor can help the algorithm to better cope with noise and abnormal values, the disturbance can make the algorithm more robust and insensitive to small changes of input data, and therefore the robustness of the algorithm is improved.
Further, in the third step, the exploration capacity of the pelargonium optimization algorithm in the exploration stage is strong, and the positions of the hunting objects are randomly generated in the search space, so that the exploration capacity of the pelargonium optimization algorithm in solving the problem of accurate search is increased, but the exploration capacity of the fire hawk optimization algorithm is weak, so that the optimizing precision of the fire hawk optimization algorithm can be improved by integrating the pelargonium optimization algorithm into the fire hawk optimization algorithm, and meanwhile, the optimal position strategy is introduced, so that the optimizing precision of the fire hawk optimization algorithm is higher in global search.
In the fourth step, the PID control parameters of the water conservancy monitoring device are optimized by using an improved fire-hawk optimization algorithm, and the specific steps are as follows:
s1, aiming at the water conservancy monitoring equipment requirement, designing an objective functionThe specific formula is as follows:
；
in the method, in the process of the invention,is the difference value between the target monitoring value of the water resource by the water conservancy monitoring equipment and the real-time value of the water resource monitoring by the water conservancy monitoring equipment,for the output value adjusted by the PID controller of the hydraulic monitoring device,is the proportional gain of the PID controller of the water conservancy monitoring equipment,is the integral gain of the PID controller of the water conservancy monitoring equipment,is the differential gain of the PID controller of the water conservancy monitoring device,the iteration times;
s2, designing a Simulink simulation transfer function aiming at disturbance of a water conservancy environment;
；
in the method, in the process of the invention,is the disturbance gain of the water conservancy environment,is a complex frequency variable;
s3, encoding PID control parameters Kp, ki and Kd into a solution of a fire hawk search space;
s4, initializing a fire hawk optimization algorithm, wherein the algorithm comprises a population scale N, a problem dimension D, the number of prey N and an algorithm search space upper boundub、Algorithm search space lower bound lbMaximum number of iterationsMax_iterInitial position of fire hawk, initial of fire hawkThe initial position is the initial value of the PID parameter, and the continuously updated population position of the hawk is the value of the PID controller parameter of the continuously optimized water conservancy monitoring device in the algorithm iteration process;
s5, determining fire hawks and prey in a search space;
s6, calculating the total distance between the fire hawk and the prey, determining the territory of the fire hawk by dispersing the prey, and configuring the searching process of an algorithm by classifying the fire hawk and the prey;
s7, simulating the behavior of fire hawks for collecting burning wood sticks from main fires and then igniting the wood sticks in a selected area, wherein the two behaviors can be used as a position updating process in a search cycle of an improved fire hawk optimization algorithm, and a position updating formula is shown in a formula (1):
（1）；
s8, simulating the movement behavior of the hunting object in the territory of each fire hawk, and designing a hunting object position updating formula as follows:
，，（2）；
in the method, in the process of the invention,is the firstThe prey quilt is the firstThe new location surrounded by the fire hawks,is the firstOnly one safe place under the fire hawk,andis a random number uniformly distributed in the range of (0, 1) for determining the movement of a prey to a fire hawk and a safe place,is a nonlinear disturbance factor.
S9, simulating the behavior that the hunting object moves to the territory of other fire hawks, and designing a hunting object position updating formula as follows:
，，（3）；
in the method, in the process of the invention,is the firstThe prey quilt is the firstThe new location surrounded by the fire hawks,for another fire hawk in the search space,is thatIn addition to the safety zone,andis a random number uniformly distributed in the range of (0, 1) and is used for determining the movement of the hunting object to other safe places outside the hawk and the territory,is a nonlinear disturbance factor;
s10, calculating an fitness value, comparing the current iterative optimal fitness value with the last iterative optimal fitness value, reserving the optimal fitness value, and reserving and determining an optimal target object, wherein the optimal target object is an optimal parameter of a PID controller of the water conservancy monitoring equipment;
s11, the current iteration numberThe self-adding step is carried out,judging whether the current iteration number reaches the maximum iteration numberMax_ iterIf the PID parameter is reached, the loop is exited, a global optimal solution is output, and three parameters distributed to the PID are allocated; otherwise, the process returns to S4.
Furthermore, in the step S1, the objective function considers the control error of the hydraulic monitoring device, the output and control process of the PID controller of the hydraulic monitoring device, and the robustness of the control error of the hydraulic monitoring device.
Further, in the S2, in this case, the objective is to make the water conservancy approach the ideal value as much as possible, so we can take the error (the difference between the target monitor value and the actual measured value) as the input of the PID controller and use the transfer function to transform and filter the error appropriately.
Further, in S4, a modified eagle optimization algorithm is initialized, and first, a plurality of candidate solutions are determinedAs location vectors for hawks and prey, a random initialization process is used to determine theseThe initial position of the vector in the search space is given by:
；
；
in the method, in the process of the invention,is the total number of candidate solutions in the search space; />Is->First->A decision variable; />Representing the initial position of the candidate solution; />And->Is->First->Minimum and maximum boundaries for the individual decision variables; />Is a [0,1 ]]Random numbers distributed uniformly.
Still further, in S5, fire hawks and prey are determined in the search space, as follows:
；
；
in the method, in the process of the invention,for the kth prey on the total number of n preys in the search space, +.>Is the ith fire eagle of the total number of N fire eagles in the search space.
Further, in the step S6, the total distance between the fire hawk and the prey is calculated by the formula:
，/>；
in the method, in the process of the invention,n is the total distance between the ith fire hawk and the kth prey, N is the total number of preys in the search space, and N is the total number of fire hawks in the search space; />And->Is the coordinates of the hawk and prey in the search space.
Further, in the step S8,is the firstOnly one safe place under the fire hawk is given by the formula:
；
in the method, in the process of the invention,is the quilt ofItem of hunting surroundingOnly fire hawks.
Further, in the step S9,is thatIn addition to the safety zone,the formula of (2) is:
；
in the method, in the process of the invention,is the kth prey in the search space.
In summary, due to the adoption of the technical scheme, the beneficial effects of the invention are as follows:
1. the process of capturing the prey by the fire hawk is simulated, the fire hawk optimization algorithm is introduced into the PID control, the PID control parameters are optimized by the fire hawk optimization algorithm, the robustness of the PID control is improved, the anti-interference capability of the PID control is improved, and therefore the control precision of the water conservancy monitoring equipment is optimized.
2. The nonlinear disturbance factor is introduced to increase the exploratory property of the algorithm, when the algorithm falls into a local optimal solution, a better solution cannot be found, the nonlinear disturbance factor can randomly change the searching direction, and the algorithm is helped to jump out of the local optimal solution to find a global optimal solution.
3. The fire hawk optimizing algorithm is improved, the pelargonium optimizing algorithm is fused in the exploration stage of the fire hawk optimizing algorithm, the optimizing precision of the fire hawk optimizing algorithm is improved, and meanwhile, the optimal position strategy is introduced, so that the optimizing precision of the fire hawk optimizing algorithm is higher in global searching.
Drawings
FIG. 1 is a step diagram of a water conservancy monitoring device control optimization method based on a meta heuristic algorithm;
FIG. 2 is a control structure block diagram of the water conservancy monitoring device;
FIG. 3 is a flow chart for optimizing PID control parameters by improving the fire hawk optimization algorithm;
FIG. 4 is a graph comparing fitness values of an improved fire eagle optimization algorithm with a standard fire eagle optimization algorithm;
FIG. 5 is a graph of improved and standard eagle optimization algorithm optimizing parameters, (a) a graph of Kp, b) a graph of ki, and c) a graph of kd;
FIG. 6 is a graph comparing the control effect of the improved fire eagle optimizing algorithm with that of the standard fire eagle optimizing algorithm for optimizing the water conservancy monitoring equipment.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention; all other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-6, the present invention provides a technical solution: a water conservancy monitoring equipment control optimization method based on meta heuristic algorithm comprises the following specific steps:
step one, determining a target monitoring range and monitoring precision of water resources by water conservancy monitoring equipment as shown in fig. 1;
step two, converting the control problem of the water conservancy monitoring equipment into a meta heuristic algorithm optimization problem, and establishing an optimized structure model and a simulation model to be optimized by adopting a PID control strategy in water conservancy monitoring control;
aiming at the disturbance requirement of water conservancy monitoring equipment, improving a fire hawk optimization algorithm, wherein the improvement comprises two parts;
d1, introducing nonlinear disturbance factors into a hunting position updating strategy of a fire hawk optimization algorithmThe formula is:
；
in the method, in the process of the invention,the number of bits in the space is searched for the algorithm,the current iteration number;
and D2, fusing the pelican optimization algorithm in the exploration phase of the fire hawk optimization algorithm, and introducing an optimal position strategy, wherein a position updating strategy formula of the improved fire hawk optimization algorithm in the exploration phase is as follows:
（1）；
in the method, in the process of the invention,is the firstOnly the new location of the fire hawk,is the firstOnly the position of the last iteration of the fire hawk,is [0,1]Random numbers within a range，For the optimal position of the current iteration,is a random integer of 1 or 2,is the firstThe prey quilt is the firstNew locations surrounded by fire hawks;
step four, optimizing PID control parameters of the water conservancy detection equipment by utilizing an improved fire hawk optimization algorithm to obtain optimal PID control parameters;
and fifthly, applying the optimizing optimal parameters to the water conservancy monitoring equipment, and automatically adjusting PID control parameters by an algorithm according to real-time feedback information of the water conservancy monitoring equipment, so that the system output reaches the target monitoring precision and range, and the water conservancy equipment is accurately controlled.
Further, the first step, the water conservancy monitoring device is mainly used for monitoring hydrologic water conservancy data, the water conservancy monitoring device can realize the omnibearing monitoring of water resources, timely and accurate data support is provided for water resource management, and a target monitoring range and monitoring accuracy are determined so as to accurately control the water resource environment.
Further, in the second step, the control problem of the water conservancy monitoring device is usually controlled by using a PID control mode, as shown in fig. 2, the structural model and the simulation model mainly include a control system target value input module, a control system monitoring and measuring module, an error value module, a PID controller module, an improved fire hawk optimization algorithm module, and a controlled object module; the control system target value input module is mainly used for inputting a target monitoring value of the water resource by the water conservancy monitoring equipment, the control system monitoring and measuring module is used for collecting a real-time value of the water resource monitoring by the water conservancy monitoring equipment, and the controlled object module is mainly used for adjusting the water conservancy monitoring equipment.
Further, the third step introduces a nonlinear disturbance factorThe disturbance factor is as followsIs a nonlinear disturbance of the center, along withAnd (3) withThe distance of the non-linear disturbance factor increases, the disturbance intensity gradually decreases, and the search space median of the non-linear disturbance factorThe value is 0.5, the nonlinear disturbance factor can help the algorithm to better cope with noise and abnormal values, the disturbance can make the algorithm more robust and insensitive to small changes of input data, and therefore the robustness of the algorithm is improved.
Further, in the third step, the exploration capacity of the pelargonium optimization algorithm in the exploration stage is strong, and the positions of the hunting objects are randomly generated in the search space, so that the exploration capacity of the pelargonium optimization algorithm in solving the problem of accurate search is increased, but the exploration capacity of the fire hawk optimization algorithm is weak, so that the optimizing precision of the fire hawk optimization algorithm can be improved by integrating the pelargonium optimization algorithm into the fire hawk optimization algorithm, and meanwhile, the optimal position strategy is introduced, so that the optimizing precision of the fire hawk optimization algorithm is higher in global search.
Further, in the fourth step, the improved fire-hawk optimization algorithm is used to optimize the PID control parameters of the hydraulic monitoring device, as shown in fig. 3, and the specific steps are as follows:
s1, aiming at the water conservancy monitoring equipment requirement, designing an objective functionThe specific formula is as follows:
；
in the method, in the process of the invention,is the difference value between the target monitoring value of the water resource by the water conservancy monitoring equipment and the real-time value of the water resource monitoring by the water conservancy monitoring equipment,for the output value adjusted by the PID controller of the hydraulic monitoring device,is the proportional gain of the PID controller of the water conservancy monitoring equipment,is the integral gain of the PID controller of the water conservancy monitoring equipment,is the differential gain of the PID controller of the water conservancy monitoring device,the iteration times;
s2, designing a Simulink simulation transfer function aiming at disturbance of a water conservancy environment;
；
in the method, in the process of the invention,is the disturbance gain of the water conservancy environment,is a complex frequency variable;
s3, encoding PID control parameters Kp, ki and Kd into a solution of a fire hawk search space;
s4, initializing a fire hawk optimization algorithm, wherein the algorithm comprises a population scale N, a problem dimension D, the number of prey N and an algorithm search space upper boundub、Algorithm search space lower bound lbMaximum number of iterationsMax_iterThe initial position of the fire hawk is the initial value of the PID parameter, and the continuously updated population position of the fire hawk is the value of the PID controller parameter of the continuously optimized water conservancy monitoring equipment in the algorithm iteration process;
s5, determining fire hawks and prey in a search space;
S6、calculating the total distance between the fire hawk and the prey, determining the territory of the fire hawk by dispersing the prey, and configuring the searching process of an algorithm by classifying the fire hawk and the prey;
s7, simulating the behavior of fire hawks for collecting burning wood sticks from main fires and then igniting the wood sticks in a selected area, wherein the two behaviors can be used as a position updating process in a search cycle of an improved fire hawk optimization algorithm, and a position updating formula is shown in a formula (1):
（1）；
s8, simulating the movement behavior of the hunting object in the territory of each fire hawk, and designing a hunting object position updating formula as follows:
，，（2）；
in the method, in the process of the invention,is the firstThe prey quilt is the firstThe new location surrounded by the fire hawks,is the firstOnly one safe place under the fire hawk,andis a random number uniformly distributed in the range of (0, 1) for determining the movement of a prey to a fire hawk and a safe place,is a nonlinear disturbance factor;
s9, simulating the behavior that the hunting object moves to the territory of other fire hawks, and designing a hunting object position updating formula as follows:
，，（3）；
in the method, in the process of the invention,is the firstThe prey quilt is the firstThe new location surrounded by the fire hawks,for another fire hawk in the search space,is thatBeyond thatThe safety zone is provided with a safety zone,andis a random number uniformly distributed in the range of (0, 1) and is used for determining the movement of the hunting object to other safe places outside the hawk and the territory,is a nonlinear disturbance factor;
s10, calculating an fitness value, comparing the current iterative optimal fitness value with the last iterative optimal fitness value, reserving the optimal fitness value, and reserving and determining an optimal target object, wherein the optimal target object is an optimal parameter of a PID controller of the water conservancy monitoring equipment;
s11, the current iteration numberThe self-adding step is carried out,judging whether the current iteration number reaches the maximum iteration numberMax_ iterIf the PID parameter is reached, the loop is exited, a global optimal solution is output, and three parameters distributed to the PID are allocated; otherwise, the process returns to S4.
Furthermore, in the step S1, the objective function considers the control error of the hydraulic monitoring device, the output and control process of the PID controller of the hydraulic monitoring device, and the robustness of the control error of the hydraulic monitoring device.
Further, in the S2, in this case, the objective is to make the water conservancy approach the ideal value as much as possible, so we can take the error (the difference between the target monitor value and the actual measured value) as the input of the PID controller and use the transfer function to transform and filter the error appropriately.
Further, in S4, a modified eagle optimization algorithm is initialized, and first, a plurality of candidate solutions are determinedAs location vectors for hawks and preys, a random initialization process is used to determine the initial location of these vectors in the search space, as follows:
；
；
in the method, in the process of the invention,is the total number of candidate solutions in the search space; />Is->First->A decision variable; />Representing the initial position of the candidate solution; />And->Is->First->Minimum and maximum boundaries for the individual decision variables; />Is a [0,1 ]]Random numbers distributed uniformly.
Still further, in S5, fire hawks and prey are determined in the search space, as follows:
；
；
in the method, in the process of the invention,for the kth prey on the total number of n preys in the search space, +.>Is the ith fire eagle of the total number of N fire eagles in the search space.
Further, in the step S6, the total distance between the fire hawk and the prey is calculated by the formula:
，/>；
in the method, in the process of the invention,n is the total distance between the ith fire hawk and the kth prey, N is the total number of preys in the search space, and N is the total number of fire hawks in the search space; />And->Is the coordinates of the hawk and prey in the search space.
Further, in the step S8,is the firstOnly one safe place under the fire hawk is given by the formula:
；
in the method, in the process of the invention,is the quilt ofFire-only hawkEnclosed firstAnd (3) hunting.
Further, in the step S9,is thatIn addition to the safety zone,the formula of (2) is:
；
in the method, in the process of the invention,is the kth prey in the search space.
In specific implementation, the scale of the fire hawk population is set to be n=20, the iteration is performed 60 times, the problem dimension d=3, the search upper bound ub=0, and the search lower bound lb=100.
Through performance tests of Matlab on a standard fire eagle optimization algorithm and an improved fire eagle optimization algorithm, the smaller the fitness is, the more superior the performance of the algorithm is represented, as shown in fig. 4, a dotted line is a fitness value curve of a PID controller of the improved fire eagle optimization algorithm, compared with a fitness value curve of a standard fire eagle optimization algorithm of a solid line, the adaptability value of the improved fire eagle optimization algorithm can be obviously found to change more quickly, the algorithm optimizing speed is indicated to be faster, the fitness value is smaller, and the algorithm optimizing precision is indicated to be higher.
As shown in fig. 5, the main objective of using the algorithm to optimize the PID controller is to find the optimal control parameters Kp, ki, kd, the speed and accuracy of searching for parameters are main, the graph (a) is the parameter Kp versus the graph, (b) is the parameter Ki versus the graph, and (c) is the parameter Kd versus the graph, as can be seen from the graphs (a), (b) and (c), the speed and accuracy of searching for parameters by the improved hawk optimization algorithm (IFHO) are much better than those of searching for parameters by the standard hawk optimization algorithm (FHO), and when the iteration is performed for 30 times, the improved hawk algorithm finds the optimal parameters and tends to be stable.
Fig. 6 is an effect diagram of optimizing PID control before and after modification of a fire hawk optimization algorithm (IFHO), realizing control of a water conservancy monitoring device, and verifying an effect through Simulink simulation, and it can be obtained from the diagram that the overshoot of the optimized PID of the modified fire hawk optimization algorithm is smaller than that of the optimized PID of a standard fire hawk optimization algorithm (FHO), and the optimized PID of the modified fire hawk optimization algorithm quickly tends to be stable, which indicates that under the modified fire hawk algorithm, the water conservancy monitoring device can ensure stability of monitoring data when encountering interference in a complex environment.
Claims (6)
1. A water conservancy monitoring equipment control optimization method based on a meta heuristic algorithm is characterized by comprising the following specific steps:
step one, determining a target monitoring range and monitoring precision of water resources by water conservancy monitoring equipment;
step two, converting the control problem of the water conservancy monitoring equipment into a meta heuristic algorithm optimization problem, and establishing an optimized structure model and a simulation model to be optimized by adopting a PID control strategy in water conservancy monitoring control;
aiming at the disturbance requirement of water conservancy monitoring equipment, improving a fire hawk optimization algorithm, wherein the improvement comprises two parts;
d1, introducing nonlinear disturbance factors into a hunting position updating strategy of a fire hawk optimization algorithmThe formula is:
；
in the method, in the process of the invention,searching for the median of the space for the algorithm, < > and->The current iteration number;
and D2, fusing the pelican optimization algorithm in the exploration phase of the fire hawk optimization algorithm, and introducing an optimal position strategy, wherein a position updating strategy formula of the improved fire hawk optimization algorithm in the exploration phase is as follows:
（1）；
in the method, in the process of the invention,is->New location of fire hawk only->Is->Only the last iteration of fire hawk, +.>Is [0,1]Random number within range,/->Optimal bit for current iterationPut (I) at>Is a random integer of 1 or 2, +.>Is->The hunting object is->New locations surrounded by fire hawks;
step four, optimizing PID control parameters of the water conservancy monitoring equipment by utilizing an improved fire hawk optimization algorithm to obtain optimal PID control parameters;
and fifthly, applying the optimizing optimal parameters to the water conservancy monitoring equipment, and automatically adjusting PID control parameters by an algorithm according to real-time feedback information of the water conservancy monitoring equipment, so that the system output reaches the target monitoring precision and range, and the water conservancy equipment is accurately controlled.
2. The method for optimizing control of water conservancy monitoring equipment based on meta heuristic algorithm according to claim 1, wherein in the second step, a control structure model and a simulation model of the water conservancy monitoring equipment mainly comprise a control system target value input module, a control system monitoring and measuring module, an error value module, a PID controller module, an improved fire and hawk optimizing algorithm module and a controlled object module.
3. The method for optimizing water conservancy monitoring equipment control based on meta-heuristic algorithm according to claim 1, wherein in the third step, after the pelican optimizing algorithm and the optimal position strategy are integrated, a position updating mode for improving the fire hawk optimizing algorithm is a mode of updating by adopting a fire hawk to follow a hunting object position.
4. Water conservancy monitoring device control based on meta-heuristic algorithm as claimed in claim 1The optimizing method is characterized in that in the third step, the disturbance factor is as followsNonlinear disturbance as center, with +.>And->The distance of (2) increases, the disturbance intensity gradually decreases, the search space median of the nonlinear disturbance factor +.>The value is 0.5.
5. The method for optimizing control of hydraulic monitoring equipment based on meta heuristic algorithm according to claim 1, wherein in the fourth step, the improved fire hawk optimization algorithm is utilized to optimize PID control parameters of the hydraulic monitoring equipment, and the specific steps are as follows:
s1, aiming at the water conservancy monitoring equipment requirement, designing an objective functionThe specific formula is as follows:
；
in the method, in the process of the invention,is the difference value between the target monitoring value of the water resource by the water conservancy monitoring equipment and the real-time value of the water resource monitoring by the water conservancy monitoring equipment, and is +.>For the output value adjusted by the PID controller of the water conservancy monitoring device, +.>Proportional gain of PID controller of water conservancy monitoring equipment, < ->Integral gain of PID controller of water conservancy monitoring equipment, < ->Differential gain of PID controller of water conservancy monitoring equipment, < ->The iteration times;
s2, designing a Simulink simulation transfer function aiming at disturbance of a water conservancy environment;
；
in the method, in the process of the invention,gain for water conservancy environment disturbance->Is a complex frequency variable;
s3, encoding PID control parameters Kp, ki and Kd of the water conservancy monitoring equipment into solutions of a fire hawk search space;
s4, initializing a fire hawk optimization algorithm, wherein the algorithm comprises a population scale N, a problem dimension D, the number of prey N and an algorithm search space upper boundub、Algorithm search space lower bound lbMaximum number of iterationsMax_iterThe initial position of the fire hawk is the initial value of the PID parameter, and the continuously updated population position of the fire hawk is the value of the PID controller parameter of the continuously optimized water conservancy monitoring equipment in the algorithm iteration process;
s5, determining fire hawks and prey in a search space;
S6、calculating the total distance between the fire hawk and the prey, determining the fire by dispersing the preyThe method comprises the steps of configuring a searching process of an algorithm by classifying fire hawks and prey in the field of hawks;
s7, simulating the behavior of fire hawks for collecting burning wood sticks from main fires and then igniting the wood sticks in a selected area, wherein the two behaviors can be used as a position updating process in a search cycle of an improved fire hawk optimization algorithm, and a position updating formula is shown in a formula (1):
（1）；
s8, simulating the movement behavior of the hunting object in the territory of each fire hawk, introducing nonlinear disturbance factors, and designing a hunting object position updating formula as follows:
，/>，/>（2）；
in the method, in the process of the invention,is->The hunting object is->New location surrounded by fire hawks, +.>Is->Only one safe place under fire hawk->And->Is a random number uniformly distributed in the range of (0, 1) for determining the movement of prey to fire hawk and safe place, +.>Is a nonlinear disturbance factor;
s9, simulating the behavior that the hunting object moves to the territory of other hawks, introducing a nonlinear disturbance factor, and designing a hunting object position updating formula as follows:
，/>，/>（3）；
in the method, in the process of the invention,is->The hunting object is->New location surrounded by fire hawks, +.>For another fire hawk in search space, +.>Is->Safety zone outside, ->And->Is a random number uniformly distributed in the range of (0, 1) for determining the movement of hunting objects to other safe places outside the hawk and the territory, +.>Is a nonlinear disturbance factor;
s10, calculating an fitness value, comparing the current iterative optimal fitness value with the last iterative optimal fitness value, reserving the optimal fitness value, and reserving and determining an optimal target object, wherein the optimal target object is an optimal parameter of a PID controller of the water conservancy monitoring equipment;
s11, the current iteration numberSelf-adding (adding) of (removing) the root>Judging whether the current iteration number reaches the maximum iteration numberMax_ iterIf the PID parameter is reached, the loop is exited, a global optimal solution is output, and three parameters distributed to the PID are allocated; otherwise, the process returns to S4.
6. The method for optimizing water conservancy monitoring equipment control based on meta heuristic algorithm according to claim 1, wherein in the fourth step, kp, ki and Kd are applied to system simulation built by Simulink after optimal PID parameters are obtained, and experimental verification effects are achieved.
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