The gyroscope is an important component of the ship, and its stable performance is crucial for the control of the ship. The Fuzzy-PID algorithm is applied to the gyro temperature control system. The MCS-51 single-chip microcomputer is used as the core component of the temperature control system. The fuzzy PID algorithm and other hardware and software design are used to realize a set of temperature acquisition and control design.
--- In the ship, the gyroscope is a key component, and the space between the gyro sphere and the gyro shell is filled with suspended liquid. The choice of the gyro sphere mass and the specific gravity of the suspended liquid should ensure that the gyro sphere can have a neutral buoyancy after the suspended liquid is heated to the operating temperature. Therefore, the temperature control system should be designed to ensure that the constant operating temperature of the liquid that heats and holds the gyro component is 700.2 ° C, because at this temperature the gyro sphere has a neutral buoyancy.
--- Traditional control methods (including classical control and modern control) are very difficult to deal with controlled objects with non-linear or inaccurate characteristics. The temperature system is a large lag system, and a large pure lag can cause system instability. A large number of application practices show that the traditional PID control has better steady-state response characteristics, but it is difficult to obtain satisfactory dynamic response characteristics. The advantage of fuzzy control is that it can get better dynamic response characteristics, and it does not need to know the mathematical model of the controlled object, which has strong adaptability, fast rise time and good robustness. However, fuzzy control also has inherent shortcomings, which are easily limited by the limited level of fuzzy rules. In this design, AT89C52 is used as the control core, and Fuzzy-PID composite control is adopted. Make up for the shortcomings of simply using the PID algorithm. The fuzzy adaptive tuning of PID parameters further improves the adaptive performance of PID control, and has achieved good results in practical applications.
How the temperature control system works
---Gyro temperature control system is mainly composed of temperature sensor, AT89C52 single-chip microcomputer, A/D signal acquisition module, thyristor output control and other peripheral circuits. The controlled object of the system is the temperature of the liquid inside the gyro component, and the actuator is a thyristor trigger circuit. The operating temperature is measured by means of a bridge. The three arms of the bridge are the resistors placed in the control system, and the fourth arm is the resistance of the gyro component to heat the temperature sensor. The signal value from the bridge is differentially amplified, filtered, and then sent to the A/D sample by the high precision integrated op amp OP07. According to the measured current terminal and voltage terminal principle, the bridge voltage signal is collected by three-wire connection method, as shown in Figure 1. This is the most practical and accurate way to measure temperature. R4, R5 and R6 are wiring and contact resistance. Due to the above three-wire connection method, the adjustment of R1 can balance the bridge including R5, and R4 can be offset by R6. Therefore, this connection is commonly used in the industry for precise temperature measurement. The control part adopts the composite control of Fuzzy-PID to make the single-chip output PWM pulse, and then control the amount of current output from the actuator to the gyro heater to realize the automatic temperature control of the gyro heater. Due to the fuzzy adaptive PID control algorithm, the system can automatically adjust the PID parameters according to the actual response of the control system without operator intervention, and change the duty cycle of the PWM output waveform. Controlling the output keeps the gyro heater's operating temperature constant and automatic control, which is the key to designing the temperature control system.
Temperature control system design
--- According to the requirements of the gyroscope fuzzy control system, the heat generated during the operation of the heater causes the temperature of the liquid in the gyro component to rise, thereby increasing the resistance of the temperature sensor (for a positive temperature coefficient thermistor), then the temperature The detecting circuit sends the temperature change signal back to the input end to compare with the given temperature, and then generates a deviation and deviation change rate signal, and performs a reasoning by the fuzzy controller to generate a signal for controlling the heater to control the heater. The block diagram of the Fuzzy-PID temperature control system is shown in Figure 2. The system is mainly composed of the controlled object, the temperature sensor detection loop, the Fuzzy-PID controller and the actuator.
â— Digital PID control design
--- Using the impulse response method to measure the transfer function of the controlled object as a first-order inertia link plus pure hysteresis.
--- where K is the object magnification factor, K = 300 ° C / 100 V; τ is the pure lag time, τ = 50 s; T is the object time constant, T = 200 s.
---SCM control is a kind of sampling control. The incremental digital PID control algorithm used by the system is:
---Δu(n)=U(n)-U(n-1)=a0e(n)-a1e(n-1)+a2e(n-2)
---a0=kp(1+T/T1+TD/T)
---a1=kp(1+2TD/T)
---a2=kpTD/T
In the formula -, T is the sampling period. The reference response curve is selected and finally determined by the experiment as the sampling period. The control software is used to implement the incremental control algorithm and output the control amount. Since the control algorithm does not need to be accumulated, the control increment is only related to the most recent n samples, so the influence is small when the malfunction occurs, and it is easier to obtain a better control effect by the weighting process. This is also the main reason why the system adopts this incremental PID control algorithm as part of the PID regulator part of the fuzzy PID controller.
â— Fuzzy PID controller design
--- Firstly, according to the theory and method of fuzzy mathematics, the operator's adjustment experience and technical knowledge are summarized into fuzzy rules in the form of IF (condition) and THEN (result), and these fuzzy rules and related information (such as the initial PID) The parameters are stored in the computer. According to the response condition of the detection loop, the deviation e of the sampling time and the rate of change ec of the deviation are calculated. The input controller uses fuzzy reasoning to perform the fuzzy operation, and the Kp, Ki, and Kd at the moment can be obtained, and the PID parameters are realized. The best adjustment.
---Fuzzy-PID controller is based on the PID parameter pre-setting, using fuzzy rules to adjust the three modified parameters △Kp, △Ki, △Kd of the PID controller online in real time to achieve optimal temperature control. The input and output variables of the fuzzy controller are all accurate, and the fuzzy reasoning is performed on the fuzzy quantity. Therefore, the controller first needs to obfuscate the input quantity. In the designed Fuzzy-PID controller, the language values ​​of the input and output variables are divided into seven language values: {NB, NM, NS, O, PS, PM, PB}, and the elements in the subset represent negative, Negative, negative, zero, positive, positive, and positive. The membership function uses a highly sensitive trigonometric function. In order to enhance the robustness of the system and improve the resolution of the membership function, the shape of the function near the value of 0 is steeper, as shown in Figure 3.
The basic domain of --e is [-100 °C, 100 °C]; the basic domain of ec is [-5,5]; the basic domain of △Kp is [-1,1]; the basic theory of △Ki The domain is [-0.002, 0.002]; the basic domain of △Kd is [-1, 1]. The fuzzy quantities of the above variables are E, EC, △KP, △KI and △KD, respectively, and the domain is [-6,-5, -4,-3,-2,-1,0,1,2 , 3, 4, 5, 6]. The quantization factors of the input quantities e and ec are: ke=0.06, kec=1.2.
--- Fuzzy control design is to sum up the technical knowledge and practical operation experience of engineering designers. The setting rules of parameters are the core of the controller. Establish a suitable fuzzy rule table and obtain three parameters for â–³Kp, â–³Ki and â–³Kd. For the fuzzy control table that is set separately, see Table 1, Table 2 and Table 3.
--- For the input deviation e and the deviation change rate ec, after obtaining the corresponding linguistic value, according to the tuning rule table, through the formula fuzzy decision, the fuzzy of the three modified parameters â–³Kp, â–³Ki, â–³Kd are obtained respectively. the amount. After the above fuzzy inference, the three correction parameters set by the Fuzzy-PID controller are defuzzified to obtain an accurate amount to calculate the output control amount, which is the percentage of the heater on and off per unit time. There are several methods for defuzzification, such as the maximum membership degree method, the center of gravity method, etc. For the controller, the center of gravity method is used to obtain the exact value of the output. The output c(k) after the fuzzy decision is obtained by the following formula.
--- where c(k)ku (ku is the scale factor of the output) is the correction parameter after auto-tuning, and the scale factor of each correction parameter is:
---Ku(â–³Kp)=1/6,Ku(â–³Ki)=1/300,Ku(â–³Kd)=1/6
--- The parameters input to the PID controller are calculated by the following equations.
---Kp=Kp'+â–³Kp,Ki=Ki'+â–³Ki, Kd=Kd'+â–³Kd
Implementation of temperature control system
â— Hardware implementation
--- For the gyroscope fuzzy control system, consider the functional requirements, separate the input and output functions of the system to determine the number of signals at the input and output of the system. For the input of the system, consider the following signals.
--- (1) Temperature detection, used to detect the output temperature of the system, that is, the temperature of the liquid in the gyro component, in order to make decisions on the control of the heater.
--- (2) Temperature setting, used to set the operating temperature of the gyro components, the temperature set for different requirements is different.
--- For the output of the system, consider the following signals.
--- (1) Heater control signal, the thyristor controls the working state of the heater.
---(2) Display the current temperature of the system to the user.
--- The hardware structure of the gyroscope temperature control system is shown in Figure 4.
--- In the control system, the high-precision integrated op amp OP07 is used to differentially amplify and filter the millivolt-level thermoelectric potential of the platinum resistor, and then send the detected voltage signal to the analog-to-digital converter AD0809, sample the value and transmit it to AT89C52.
--- The P0 port of AT89C52 is the data line, which is connected to the data port of AD0809 and LCD. The 5 control lines of the P2 port control the LCD, the P1.0 and P1.1 control alarm indicators, and the P1.2 to P1.4 ports are used to control the thyristor. Then, through the Fuzzy-PID controller, the duty cycle of the PWM pulse is calculated, and the load voltage is controlled to finally complete the temperature control of the liquid in the gyro component.
â— Software implementation
--- The software block diagram of the gyroscope temperature control system is shown in Figure 5. At power-on reset, the system initializes. The site temperature is then detected and forced by the system for a period of time during the warm-up phase. Then, according to the detected temperature, output control, alarm indication, display, and the like are generated. The main part of the whole program is written in assembly language, and the function written in C language is called in the control algorithm part. The system uses the entire control algorithm as a function for assembly language calls.
Conclusion
--- Applying the Fuzzy-PID algorithm to the gyro temperature control system, the design goal is to make the transition time of the system as short as possible and improve the control effect under the same control precision conditions. The composite control is adopted to make the system effectively suppress the influence of pure lag, and the robustness is strong. When the parameters vary greatly and there is interference, the control effect can still be achieved.
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