Simulation and Analysis of Cascaded PID Controller Design for Boiler Pressure Control System

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1 PAPER ID: IJIFR / V1 / E10 / ISSN (Online): An Enlightening Online Open Access, Refereed & Indexed Journal of Multidisciplinary Research Simulation and Analysis of Cascaded PID Controller Design for Boiler Pressure Control Mr. Rajesh Kondareddy Assistant Professor, Department of Instrumentation Engineering Kokrajhar, Assam, India Abstract The paper will assist in evaluating the impact and performance of cascaded PID controller designs for the pressure control of an industrial boiler system. From the control system compositions, it is clear that simple PID controller is an obsolete for the control of non-linear processes parameters like pressure. PID controller in cascaded design is the desirable choice compared to conventional closed loop control system for controlling these non-linear processes. However, it is constrained in choosing the better PID gains values. Hence, this paper is simple approach to set the better values of PID gains constants in cascaded form by evaluating the performance with conventional simple tuning formulas. performance analysis of various algorithms was carried out by finding the system s static and dynamic performance characteristics in each case. The entire system is modeled by using MATLAB/ Simulink, The simulation results indicate that the proposed cascaded PID control system design could results to rapidity in response with static and robust dynamic performance. Keywords Cascaded Control, Dynamic performance analysis, PID (Proportional plus Integral plus Derivative) controller, pressure process control, Matlab/Simulink, Tuning concepts. 1 Introduction The main advantage with PID controllers is that by using two PIDs together, which achieves a better dynamic performance compared with single PID. This is known as cascaded PID controller. In this controller, the two PIDs are placed in such a way that the set point of one PID is controlled by another PID. One PID controller works as secondary(inner loop)controller which takes the output of another PID as a set point. Another PID works as Primary(outer loop) controller which controls the basic Industrial physical parameters, such as level, temperature, pressure, flow etc. Hence, cascaded PID controller increases the controller working frequencyand reduces the time constant of the system. Cascade control system has some distinguishing features., like Quality control, Antiinterference, ability, flexibility and quickness. So it is generally used in Longer delays, larger load changes and nonlinear controlled objects The cascade control system contains couple of control loops. They are primary loop and secondary loops. The primary loop monitors the controlled variable and uses deviation from its set point to provide an output to the secondary loop. The secondary loop Copyright IJIFR 2014 Author s Subject Area: Instrumentation Engineering Available Online at:

2 receives its set point from the primary loop and controls the set point variable accordingly. In process industries such as thermal power plants, refineries, steel plants, etc., Boiler is the most important pneumatic & thermal equipment used. Hence some basic methods have been recognized for automatic control of boiler stream pressure. For example, constant control of boiler process variables, cascade control of temperature in the boiler and flow of the pre-heated liquid, the control of pre-heated liquid temperature and also regulating boiler stream pressure. So far, the control focus has moved to performance optimization & suppressing the disturbances. The pre-heated liquid flow control primarily regulates the Boiler stream pressure. Cascaded PID controller is well suited because the control of pre-heated liquid flow in the boiler is a typical process and larger capacity lag in the boiler stream pressure control system. The dynamic quality of the entire system will be improved by pre-regulating the interference which influences the intermediate variables. The effectiveness of control of cascade control system is more efficient than single loop control system. However it has some drawbacks since cascade control are multiple control loops, makes physical and computational architecture more complex, sensors can be costly additional controllers etc. 2 Boiler Cascade Control The constituents of a boiler pressure control system are shown in figure.1. Whereas PIC is primary controller, LIC is secondary controller, PT represents measure of pressure for the exports of raw materials, and LT represents measure liquid level of the boiler. The basic operation of the boiler pressure control system is as follows. Figure.1 Cascaded control of Boiler Pressure system The output of the primary controller (PIC) is given as set point to the secondary controller (LIC), LIC controls the pre-heated liquid flow. In the process, liquid which is entering in the boiler is heated up to a specified temperature to produce stream. From fuel Combustion chamber to the raw material export, there are three capacity components in temperature. They are boiler column, heater heat exchange rate and liquid flow inlet. Disturbances of load are the system disturbances in one side and on the other side are the disturbances in the heater, such as temperature in boiler, inlet liquid temperature and its pressure. pre-heater liquid is used to eliminate sudden heat transfer 118

3 problems and even heat distribution and also used as distillation process. In the control system, the primary object is the outlet stream pressure and the secondary object is the liquid level in the boiler. The main controlled variable is the stream pressure and sub controlled variable is the liquid flow rate in the boiler. The primary disturbances are temperature in the boiler. The secondary disturbances are the valve position, inlet liquid pressure, current to pressure converter (I/P). One of the important prevention that must be taken in cascaded PID control system is that, in the selection of design parameters ensure that there is no matching problem of time constants of primary and secondary loops (sub-loops). So that safe operation preventing resonance can be possible. 3 Design Cascaded PID Control The equations 1 and 2 are the transfer functions for Primary and secondary objects. G 1 (s) = 0.2/s s+1.25 (1) G 2 (s) =0.125/s s +2.5s+3.2 (2) The boiler cascade PID control system is shown below. Figure: 2 Boiler cascade PID control system This system is implemented in MATLAB/Simulink as shown in the figure:3. The equation.3 shows the mathematical representation of the PID controller and table.1 shows the effect of increasing K p, K i, and K d gains on dynamic characteristics. Where., U(t) = control signal applied to the plant K p = proportional gain constant K i = K p /T i = integral gain constant K d = K p T d = derivative gain constant 119

4 Table.1 Effect of increasing P, I, and D gains on dynamic characteristics Parameter Rise time(t r ) Overshoot(M p ) Settling time(t s ) Error(e ss ) K p Decrease Increase Small Change Decrease K i Decrease Increase Increase Decrease Significantly K d Minor Decrease Decrease Decrease No Effect Hence, the PD controller is used to have fast settling and reduce damping; PI controller is used to have less steady state error and increases gain. And PID controller is used to have all individual control actions. Hence, different combinations of controllers should be selected properly to get the desired characteristics. This paper uses ultimate gain/ultimate cycle methods for PID parameter tuning Figure.3 MATLAB/Simulink model of cascaded PID controller design for furnace temperature control 4 Ultimate Cycle Method For Tuning Of PID Controller Gains The ultimate cycle methods are the simple and more effective ways for setting up the PID controller gains. Basically, these methods are of three types, mentioned as follows. *Ziegler-Nichols (ZN) PID controller tuning method. *Modified Ziegler-Nichols PID controller tuning method. *Tyreus-Luyben (TL) PID controller tuning method. The furnace temperature in the industrial production has non-linear, time-varying and delay characteristics. Hence, we cannot create an absolute mathematical model. It is always a painful and challenging task to select proper values for K p, K i, and K d gains. To reduce the above problems and to 120

5 improve transient response specifications, the outer loop PID is tuned by using tuning algorithms. Tuning of PID controller involves the best selection of values for proportional (K P ), integral (K i ) and derivative (K d ) gains. The following are the steps to calculate critical gain (K c ) and critical time period (T c ). Figure.4 shows the process flow of PID controller gain settings. Following are the steps to find K c and T c i. Reduce integral and derivative actions to their minimum effect or zero i.e. design the system with proportional controller only and with unity feedback. ii. Gradually begin to increase the proportional gain value until the system exhibits the sustained oscillations. iii. This gain at which the system obtain steady cycling or sustained oscillations about the set point is called critical gain (Kc). The time period corresponding to these oscillations is called as critical time period (T c ). iv. Note the values of these K c and T c. v. From these values, calculate K p, K i, and K d gain values based on the method considered as shown in the Table.2. Table.2 Controller gain parametrs of different control techniques Parameter Ziegler-Nichols PID Controller Tunning Formula Modified Ziegler-Nichols PID Controller Tunning Formula Tyreus-LuyBen PID Controller Tuning Formula Ti T i =T c /2 T i =T c *0.9 T i =2.2*T c T d T d =T d /8 T d =T d /2.5 T d =T d /6.3 K p K p =0.6*K c K p =0.3*K c K p =0.44*K c K i K i = K p / T i K i = K p / Ti K i = K p / Ti K d K d = K p / T d K d = K p / T d K d = K p / T d Figure.5 shows, the overall MATLAB/Simulink model for PID controller design with different tuning methods. The parameter gain values obtained for different PID controllers are listed in Table.3. Figure.6 shows the elaborated design of the furnace system with Ziegler-Nichols PID controller. Table.3 P, I, D parameters obtained for various tuning formulas S.No Method Names K p T i K i T d K d 1 Ziegler- Nicholas(ZN) tuning formula 2 Tyreus-Luyben tuning formula 3 Modified Ziegler Nichols Tuning formula

6 Figure.4 Flow chart of PID tuning process narrates in finding controller parameter constants by getting critical gain(k c ) and critical time(t c ) in Z-N method. Figure.4 Flow chart for PID tuning method Figure.5 Comparison model for all the methods. 122

7 5 Dynamic Performance Characteristics The change of response of a closed loop system with respect to time is called as dynamic response [8]. This time response can be analyzed by calculating the following parameters. *Rise time (T r ): The Rise time refers to the time required for the response of the system to reach from a low value to a high value. Typically, these values are 10% and 90% of the steady state value respectively and in second order system, it depends on damping ratio. *Delay-Time (T d ): The delay time refers to the time required for the response of the system to reach from zero to 50% of the steady-state value for the first time. *Settling Time (T s ): The settling time refers to the time taken for the response to reach and remains in a specified error band. The tolerable error band is usually (2-5) % of the steady-state value. *Steady-state Error (e ss ): The steady-state error is the difference between the actual response and desired response when the system reaches the steady state. *Peak overshoot (M p ): The peak overshoot refers to the ratio of first peak value measured from steady-state value to the steady-state value. *Peak Time (T p ): The peak time refers to the time taken by the response to reach the first peak overshoot. *Stability: A system is said to be stable if the system produces bounded output for a bounded input. The ideal response of the system will have quick rising, minimum delay time, zero steady-state error, quick settling, minimum overshoot, and stability. 6 Simulation Results Figure.6 shows the formation of output response of cascade PID system about the set point.figure10 shows the comparative result for all the responses. The transient response/dynamic performance characteristics are calculated and tabulated as shown in the table.4. Figure.6 Sustained oscillations about set point Figure.7 response with Cascade Z-N PID Controller 123

8 Figure.8 response with Cascade Modified Z-N PID Controller Figure.9 response with Cascade T-L PID Controller Figure.10 Comparison of all responses 124

9 Table.4 Comparison of different time domain specifications Time Domain Performance Parameters S.No Method Names Delay Time(T d ) in Sec Rise Time(T s ) in Sec Settling Time(T s ) in Sec Peak Overshoot(M p ) In % Transient Behavior % Steady state Error (e ss ) 1 Ziegler- Nichols(ZN) tuning formula 2 Tyreus-Luyben % oscillatory % oscillatory 0 Tuning formula 3 Modified Ziegler Nichols Tuning formula % oscillatory 0 7 Conclusion In the paper firstly, the Simple PID controller is used as temperature process controller for Industrial heating furnace. Later on various tuning methods are used to tune the cascaded PID controller gain parameters. The performance of all is evaluated against each other and tabulated as Table. 4. From the table, the following points can be observed. *Even though, the Ziegler-Nichols PID controller produces the response with lower delay time, rise time and settling time, it has severe oscillations with a very high peak overshoot of 59.20%. This causes the damage in the system performance. *In the case of Tyreus-Luyben PID Controller, the values of delay time, rise time, and settling time are better in comparison with Modified Ziegler-Nichols method, and almost identical to the Ziegler- Nichols method. Also, it offers major advantage in terms of smooth transient behaviour and less overshoot. *Hence, it is concluded that the Tyreus-Luyben tuning method is best suited for setting up the values of given cascaded PID controller system and gains, to be used for controlling non-linear processes such as temperature. 8 References [1]. Liu Jinkun, MATLAB Simulation of Advanced PID Control [M], Electronic Industry Press, Beijing, 2006, pp [2]. Ge Lusheng Tao Yonghua, and Yin Yixin, New Type of PID Control and Its Application [M], 2000, pp [3]. Tang Xianlun, Li Yinguo, Chou Guoqing,,and Cao Xiu, the PID algorithm in cascade control system based on MATLAB, Chongqing University,2005 (9): [4]. Guo Lin,Jin Jing, the new PID parameters selection in the furnace control applications, industrial instrumentation and automation equipment, 2010(1): [5]. Zhuzhen wang, Xiaodong Zhao, and Haiyan Wang, Design of series leading correction PID controller, In the proc. of IEEE International Conference, 2009 [6]. Wang Zhenglin, Guo Yangkuan,. Process control engineering and simulation. Beijing: Electronic Industry 125

10 Press, [7]. Duan Baoyan, Su Yuxin, A new nonlinear PID controller. Control and Decision, 2003, 18 (1) : [8]. Curtis D Johnson, Process Control Instrumentation Technology, Pearson Education, [9]. R.C. Dorf and R.H. Bishop, Modern Control s, Addison-Wesley, Reading, [10]. K.J. Åström, Introduction to Stochastic Control Theory, Academic, New York, [11]. D. Graham and R.C. Lathrop, The synthesis of optimum response: criteria and standard forms II. Trans. AIME, vol. 72, pp , [12] I. Kaya, Relay feedback identification and model based controller design, Ph.D. Thesis, University of Sussex, U.K,

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