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2011 International Conferenceo n Electronic&Mechanical EngineeringandInformation Technology

The Application of Co Simulation Based on AM ESim and Matlab in Electrohydraulic Servo SystemY o n g l i n g F u 1 , D i a n l i a n g F a n2

School of Mechanical Engineer ing and AutomationBeihang Univers i ty

Beij ing, Chinafuyongling@126.com, fandianliang@sina.com

H a i t a o Q i 1 , W e i h o n g W a n g 2School of Automation Science and Electr ical Eng ineer ing

Beihang Univers i tyBeijing, China

ha i tao8642@ 163.com, he - b i@ l63. com

AbstractThe structure and operating principle of Electro-hydraulic servo system were described, and the Co-Simulationbased on AMESim and Matlab was performed. Furthermore,aiming at the problem that construction of an accurate modelof an Electro-hydraulic servo system based on traditionallinear methods remains a difficult task due to its nonlinearcharacteristics including flow/pressure relation , etc, the paperproposed a data-driven control method based on the model-free adaptive control. The simulation results show that themodel-free adaptive control method satisfies the performanceof servo control system, and provides the electro-hydraulicservo control system with new ideas and new methods.

Intex Terms Electro-hydraulic Servo System; AMESim;Matlab; Co-Simulation; Model-Free Adaptive Control;I. INTRODUCTION

Electro-hydraulic servo control sys tem has manynonlinear features, for example the load flow of the servovalve is a nonlinear function of spool displacement, oilsupply pressure and load pressure, and it is of greatinfluence to the amplification in the front of the servosystem, and s imultaneously f r ic t ion between the mechanicalagencies, the damping coefficient of the system, viscosityand elasticity of the oil are nonlinear or time varying. Underthe condit ions , t radi t ional control methods can not meet therequirements of precision control, and anti- interferenceability is poor. The traditional PID controller is effectivewhen the l inear model of the control led system changewithin a very small range. Though the tradi t ional compositecontrol scheme can be achieved within a cer tain range ofhigh control precision, the control parameters of theadjustment is very cumbersome and it is difficult to f ind theoptimal parameters . Therefore, adopting a new controlmethod that does not re ly on the system model has becomethe urgent requirements of the new generat ion of highprecision load simulator.

Data-dr iven control method is one of the theor ies andmethods of control that aroused and developed to solve theproblems of modern control method which dependent on thenature mathematical model and it is a control theory in anew direct ion. When the global mathematical model of thecontrol led system is completely unkno wn, or the uncer taintyof the model of the controlled system is large, or when thecontrolled process has significant structural changes, it isdifficult to use a mathematical model to express it; When

the cost of modeling and control is poor , or the mechanismmodel of the controlled system is too complex, order is toohigh, analysis and design are inconvenience in pract ice, weshould consider the application of data-driven control theoryto solve the pract ical control problems[ l] . Currently, Data-driven control method has been successfully applied in themold, motor control , chemical process control , urbanexpressway traffic control, and the fields of sheet metalforming. Practical application, simulation and theoreticalproof all indicate that such methods are able to deal withs trong nonlinear and t ime-varying control sys tems.

The exis tence problems with the modern control theoryare on two issues, these are the dependence of the structureof the control led system and dynamics modeling. The data-dr iven control method is produced and develops quicklywith the aim of solving the essentia l problem of moderncontrol theory. The definition of data-driven control is:control ler des ign model does not contain information aboutthe mathem atical model of the control led process , control ledsystem using only the online and offline I /O data and theknowledge gained f rom process ing data to design thecontroller , and under certain assumptions, the control theoryand methods is in the nature of convergence, stability,security and robustn ess [1 ]. In short, data-driv en controlmethod is a controller designed directly from the data to thecontrol method.

AMESim has r ich model l ibrary, and has greatadvantages on Modeling and Simulat ion for the hydraulicsystem. Users can build a custom module or s imulat ionmodel in accordance with the actual physical sys tem inAMESim. Simulink calculates by means of Matlabfunctions, and the control model can be established moreaccurately and programs wr i t ten in Matlab are also moreaccurate , AMESim provides the inter face with the Matlab,Their Co-Simulat ion, not only makes AMESim playprominent role in hydraulic components s imulat ioncapabil i t ies , but a lso enables a more complete systemsimulat ion resul ts with powerful numer ical process ingcapabilities of Matlab / Simulink, and it is an effectivesolut ion to the problem of s imulat ion techn ology.

II. S T R U C T U R E O F E L E C T R O - H Y D R O U L I CS E R V O S Y S T E M

Structure of linear actuator load test system we studied is

978-l-61284-088-8/ll/ 26.00 2011 IEEE 3547 12-14 August,2011

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Loading Cylinder 2. Force System Servo Valve 3.Force Sensor 4.D isplacement Sensor5.Displacement System Servo Valve 6. LVDT 7. Subjects Cylinder

Figure 1. loaded with the test system schematicconsisting of loading system and actuator system, executecomponent is loading cylinder , and control component usesflow servo valve, and detect loading force by the forcesensor.

As shown in Figure 1, the left is the loading system, andthe right is the actuator system (linear actuators) . Testing ofactuator system can be divided into no-load test and loadtest, and if it is a no-load test, then the actuator system isonly a position servo control system, however, with regardto loading system, it is divided into static loading anddynamic loading, and while s ta t ic loading the actuatorsystem does not move, now this loading system is a forceservo system. If the actuator system moves according to itsown expected steering trajectory as well when loading andat this time it is a dynamic load, now in terms of the loadingsystem it is a force servo system with perturbation position.At this t ime, to overcome the problem of extraneous forcebecomes the main problem of the loading system. Therefore,the system has three control problems, they are as follows:position servo control; force servo control; extraneous forcecontrol. This paper focuses on position servo control only.

System is provided with a 2IMP high-pressure by oi lsource, there are two accumulators on the oil distr ibutionstation, which can absorb the oil pressure fluctuation of theoil source, after this the oil run into the servo valve. LVDTdetects the displacement of pis ton rod; Displacementtransducer conver ts the value of the convers ion by sample,and then sent to the computer. After the computerconverting the signal that is calculated by the A/Dconversion, the signal is added to the input of the servoamplifier in the form of voltage, servo amplifier convertsthe input voltage into current signal output to drive the servovalve, by adjusting the opening of the servo valve to controlthe flow of hydraulic cylinder, create the movement of thepiston, and so control the displacement.

I II . D A T A - D R I V E N C O N T R O L M E T H O D - M O D E L -F R E E A D A P T I V E C O N T R O L

For nonlinear systems with general structure:y(k + l) = f(y(k),y(k-l),-,y(k-ny),

u(k),u(k -l),'-,u(k -nu)) (1)W her e y(k) , u(k) respectiv ely stands for outpu t and

input of the system at the time k; n , nu are the order ofthe sys tem tha t i s unknow n; / ( ) is a non linear functionthat is unknown.Assumption 1: System (1) is a sys tem that the input andoutput can be observed and controlled, that is to say:uniformly bounded desired output s ignal yr (k + 1) of asystem, have possible exis tence of uniformly boundedcontrol input signal, in which control makes the systemdriven by the input signal is equal to the output of thesystem desired output.As sum ptio n 2: / ( ) is continuous on par t ia l der ivat ivesof the input signal of the current control system.Assumption 3: System (1) is general ized Lipschitz , that isto s ay, if there is an arb itrary k an d Az/(A;) ^ 0 , theinequa lity is obtaine d, in theinequa l i ty A ^&+1)=y{k+ \)-y{k\/Su{k) =u(k)-u(k-l),and b is a constant.Note 1: These three assumptions above are not harsh,assumption 1 is a bas ic assumption of the control led system,if it is not satisfied, and the control of such systems is notpossible . Assumption 2 includes a large class of nonlinearsystems. Assumption 3 is a limit to the variation output ofthe system, That is , bounded changes in the input energysector produce bo unded changes in the output energy sector,and apparently, it includes a class of nonlinear systems.Theorem 1: The nonlinear system (1), satisfy theassum ption s 1 to 3, so if |Au(k)\ * 0 , The re is a certain(j)(k) cal led 'Pseudo-par t ia l-der ivat ive , PP D' , w hichmakes Ay(k+l)=0(k)Au(k) (2)In addit ion U( k) \ < b, where b is constant.

Detai ls of the proof of Theorem 1 which is non-parametr ic l inear t ime-varying dy namic can be seen in [2] .

Consider the following control input criterion function:j(u(k))=\y k+l)-y k+l)f+l\u(k)-u(k-lf (3)W her e y (k +1) is the expectat ion of t racking s ignal

of the system, X is a positive weight coefficient, y{k) ,u(k) respective ly stand for outpu t and input of the systemat the time k. This criterion function because of theintroduction of X \u{k) u{k 1) , mak es the changesin the input of the control is limited, and overcomes thesteady-state tracking error.

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Substitute (2) into the criterion function (3), solute theder ivat ion ofu(k) , and make it equal to zero, therefore,

u(k)=u(k-\) + Pfk\2(y(k +\)-y(k)) (4)A +\0(k)\Where p is a sequence of steps.Since /) k) is a pseud o-partial de rivative of the system ,

and is unknown, therefore, it can not be directly applied to(3) . We use the online (j)(fc) which is es t imated by (j){k),and give the expression for the control algorithm:u(k)=u(k-l)+ P />[k) (y(k +l)-y(k)) (5)A +U(k)\

Pseud o-partial deriva tive of the estimated c riterionfunction is:Akk)) = \y k)-y k-1 -ck)Au k-l f

+M\kk)-kk-l) (6)W her e y(k) represents the actual outpu t of the system,

j>(fc) is the estimated value o(j)(k) , |i stands for the stepsize parameter.

With (2) and (6), according to the optimal conditionspar t ia l der ivat ives of pseudo-algor i thm can be es t imated,

^~ l)JAy(k) - 0(k - 1) An(*-1)] (7)ju + Au(k-\)Where n stands for a sequence of steps, and | i is the

weighting factor.I V . C O - S I M U L A T I O N A N D D I S C U S S I O N

Control sys tem modeling includes hydraulic systemmodeling and preparat ion of control a lgor i thm. Cylindercontrol valve and hydraulic system modeling uses AMESim,and Matlab software is used for writing control algorithm.A. hydraulic system modeling in AMESim

There are four steps to model and simulate thehydraulic system, they are as follows:(1 ) Sketch Mode: Select the appropriate graphics

module from different elements library to builda system model;

(2 ) Submo del Mo de: Designate cor respondingmathematical model for each graphics module;

(3 ) Pa ra meter Mo de: Set the cor respondingparameters for each graphics module;

(4 ) Simulat ion Mod e: Run the s imulat ion andanalysis of simulation results;

Figure 2. the system model based on AMESimAs shown in Figure 1, the compo sit ion and pr inciple

of the loading system and the actuator system, the papercreates electro-hydraulic position servo control systemmodel shown in Figure 2 in AMESim. In Figure 2, a l l thehydraulic components are supplied f rom the hydraulicsystem of the s tandard components l ibrary in the modelselection. Controller module is the interface modulebetween AMESim and Matlab, through which you canoutput the control information in the Simulink to the servovalve; meanwhile , the Hydraulic models can also back thesensor information to the Simulink controller . Interfacemodule is the s tandard module supplied by AMESim, theinput and output number of the s ignals of the module needto be defined by you according to the need of the system.

In the Simulat ion and modeling, set the mainparameters of the system com ponen ts as fol lows:

Servo valve: moo g servo valve, ra ted f low 2 5L/min,response frequency 80Hz, damping ratio 0.8, deadband0 . 1 % , zero leakage 1.2xl0 ^mm/min;

Hydraulic cylinder: piston inertial mass 10kg, pistonrod diameter 90m m, pis ton displacemen t 40m m,coefficient of visco us friction B=20 00N .s/m.B. Establish controller mode l in Matlab/Simulink

As shown in Figure 3, in Matlab / S imulink the modelof hydraulic system is in an S-function module. The nameof S-function module is the name of the hydraulic f ilecreated in AMESim, the ent ire process of Co-Simulat ioncontrol led by the Simulink, when s imulat ion the hydraulicsystem model Transfers to Simulink, and solves thes imulat ion with the solver provided by Matlab. Model- f reeadaptive control ler achieved by the Matlab function wr i t tenin the M-file which transfers to Simulink as well.

With the pseudo-par t ia l der ivat ive es t imation algor i thmand control law previously obtained, MFAC control schemecan be given as follows:

r/Au{k-\)ju + Au(k-l)

j) k) =(l)(k-\)+~[Ay k)- k- \)Au(k -1)] (8)

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0(k) = (l), if0(k)