Available online at ScienceDirect. Procedia Technology 22 (2016 )

Similar documents
3.1 Experimental Design

Chapter 2 Introduction to the Stiffness (Displacement) Method. The Stiffness (Displacement) Method

Control Systems of a Non-stationary Plant Based on MPC and PID Type Fuzzy Logic Controller

A Model-Free Adaptive Control of Pulsed GTAW

Module 4. Analysis of Statically Indeterminate Structures by the Direct Stiffness Method. Version 2 CE IIT, Kharagpur

The analysis of scoring matrix in voting system with multiple criteria and multiple places

MODELLING, SIMULATION AND ROBUST ANALYSIS OF THE TEMPERATURE PROCESS CONTROL

Computations of the Shock Waves at Hypersonic Velocities Taken into Account the Chemical Reactions that Appear in the Air at High Temperatures

Feedback-error control

Design of NARMA L-2 Control of Nonlinear Inverted Pendulum

Modeling and Optimization of propylene polymerization with branching

STATIC, STAGNATION, AND DYNAMIC PRESSURES

MODELING THE RELIABILITY OF C4ISR SYSTEMS HARDWARE/SOFTWARE COMPONENTS USING AN IMPROVED MARKOV MODEL

A KINEMATIC WAVE MODEL FOR EMERGENCY EVACUATION PLANNING

NEURAL CONTROL OF NONLINEAR SYSTEMS: A REFERENCE GOVERNOR APPROACH

MODULAR LINEAR TRANSVERSE FLUX RELUCTANCE MOTORS

Statics and dynamics: some elementary concepts

ASPECTS OF POLE PLACEMENT TECHNIQUE IN SYMMETRICAL OPTIMUM METHOD FOR PID CONTROLLER DESIGN

Theoretical and Experimental Implementation of DC Motor Nonlinear Controllers

Magnetostrictive Dynamic Vibration Absorber (DVA) for Passive and Active Damping

Oil Temperature Control System PID Controller Algorithm Analysis Research on Sliding Gear Reducer

Chebyshev Affine Arithmetic Based Parametric Yield Prediction Under Limited Descriptions of Uncertainty

On Fractional Predictive PID Controller Design Method Emmanuel Edet*. Reza Katebi.**

Partial stabilization of a class of hydraulic mechanical systems with Casimir functions

Study on the impulsive pressure of tank oscillating by force towards multiple degrees of freedom

Linear and Nonlinear Model Predictive Control of Quadruple Tank Process

ME 375 System Modeling and Analysis. Homework 11 Solution. Out: 18 November 2011 Due: 30 November 2011 = + +

Inter-Ing 2005 INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC CONFERENCE WITH INTERNATIONAL PARTICIPATION, TG. MUREŞ ROMÂNIA, NOVEMBER 2005.

On Line Parameter Estimation of Electric Systems using the Bacterial Foraging Algorithm

A manufacturing network design model based on processor and worker capabilities

Estimation of Lateral Displacements for Offshore Monopiles in Clays based on CPT Results

A Simulation-based Spatial Decision Support System for a New Airborne Weather Data Acquisition System

Radar Dish. Armature controlled dc motor. Inside. θ r input. Outside. θ D output. θ m. Gearbox. Control Transmitter. Control. θ D.

CONTROL SYSTEM WITH AIR BLEED FLAPS FOR SUPERSONIC AIR INTAKES

FRONT TRACKING FOR A MODEL OF IMMISCIBLE GAS FLOW WITH LARGE DATA

Simplified Identification Scheme for Structures on a Flexible Base

Wolfgang POESSNECKER and Ulrich GROSS*

Chapter 1 Fundamentals

Bayesian System for Differential Cryptanalysis of DES

Indirect Rotor Field Orientation Vector Control for Induction Motor Drives in the Absence of Current Sensors

A Simple Fuzzy PI Control of Dual-Motor Driving Servo System

Journal of System Design and Dynamics

LINEAR SYSTEMS WITH POLYNOMIAL UNCERTAINTY STRUCTURE: STABILITY MARGINS AND CONTROL

ANALYTICAL MODEL FOR THE BYPASS VALVE IN A LOOP HEAT PIPE

FEA Solution Procedure

Gravity Waves in Shear and Implications for Organized Convection

By Dr. Salah Salman. Problem (1)

Research on Longitudinal Tracking Control for a Simulated Intelligent Vehicle Platoon

Pretest (Optional) Use as an additional pacing tool to guide instruction. August 21

APPLICATION OF ENERGY ABSORBING CONNECTERS TO STEEL CONTINUOUS GIRDER BRIDGES

COMPARISON OF VARIOUS OPTIMIZATION TECHNIQUES FOR DESIGN FIR DIGITAL FILTERS

Estimation of the large covariance matrix with two-step monotone missing data

3.4 Design Methods for Fractional Delay Allpass Filters

A MIXED CONTROL CHART ADAPTED TO THE TRUNCATED LIFE TEST BASED ON THE WEIBULL DISTRIBUTION

FLOW RATE CONTROL OF VARIABLE DISPLACEMENT PISTON PUMP USING GENETIC ALGORITHM TECHNIQUE

Observer/Kalman Filter Time Varying System Identification

System identification of buildings equipped with closed-loop control devices

Robust Performance Design of PID Controllers with Inverse Multiplicative Uncertainty

The Motion Path Study of Measuring Robot Based on Variable Universe Fuzzy Control

ME scope Application Note 16

FE FORMULATIONS FOR PLASTICITY

PCA fused NN approach for drill wear prediction in drilling mild steel specimen

Open Access Stability Analysis of Internet Congestion Control Model with Compound TCP Under RED

Elasto-Plastic EFGM Analysis of an Edge Crack

Dynamic Optimization of First-Order Systems via Static Parametric Programming: Application to Electrical Discharge Machining

Elements. Using ABSTRACT. 1. Introduction. Anish Bangalore, India. tioned devices. often consist packed. This offering both.

THE 3-DOF helicopter system is a benchmark laboratory

Elements of Coordinate System Transformations

Combining Logistic Regression with Kriging for Mapping the Risk of Occurrence of Unexploded Ordnance (UXO)

Inter-Ing 2005 INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC CONFERENCE WITH INTERNATIONAL PARTICIPATION, TG. MUREŞ ROMÂNIA, NOVEMBER 2005.

Multivariable Ripple-Free Deadbeat Control

COMPUTING SCIENCE. University of Newcastle upon Tyne. Behaviour-Preserving Transition Insertions in Unfolding Prefixes. V.

Linear diophantine equations for discrete tomography

MODEL-BASED MULTIPLE FAULT DETECTION AND ISOLATION FOR NONLINEAR SYSTEMS

State Estimation with ARMarkov Models

Estimation of dynamic behavior and energy efficiency of thrust hybrid bearings with active control

2-D Analysis for Iterative Learning Controller for Discrete-Time Systems With Variable Initial Conditions Yong FANG 1, and Tommy W. S.

Lower Confidence Bound for Process-Yield Index S pk with Autocorrelated Process Data

Temperature, current and doping dependence of non-ideality factor for pnp and npn punch-through structures

Chapter 3 MATHEMATICAL MODELING OF DYNAMIC SYSTEMS

A PIEZOELECTRIC BERNOULLI-EULER BEAM THEORY CONSIDERING MODERATELY CONDUCTIVE AND INDUCTIVE ELECTRODES

Uniformly best wavenumber approximations by spatial central difference operators: An initial investigation

Effect of Delay in Predation of a Two Species Allelopathic System Having Imprecise Growth Rates

Multivariable Generalized Predictive Scheme for Gas Turbine Control in Combined Cycle Power Plant

Distributed Rule-Based Inference in the Presence of Redundant Information

ANALYTIC APPROXIMATE SOLUTIONS FOR FLUID-FLOW IN THE PRESENCE OF HEAT AND MASS TRANSFER

Available online at ScienceDirect. Procedia Engineering 102 (2015 )

Identification of Factors Affecting Educational Performance of Nigerian Adult Learners: A Preliminary Study

An Investigation on the Numerical Ill-conditioning of Hybrid State Estimators

I Poles & zeros. I First-order systems. I Second-order systems. I E ect of additional poles. I E ect of zeros. I E ect of nonlinearities

MODELING OF THE DYNAMIC RESPONSE OF A FRANCIS TURBINE

Study on a Ship with 6 Degrees of Freedom Inertial Measurement System and Related Technologies

Fuzzy Control of a Nonlinear Deterministic System for Different Operating Points

Participation Factors. However, it does not give the influence of each state on the mode.

Churilova Maria Saint-Petersburg State Polytechnical University Department of Applied Mathematics

Pressure coefficient evaluation on the surface of the SONDA III model tested in the TTP Pilot Transonic Wind Tunnel

H-infinity Model Reference Controller Design for Magnetic Levitation System

Intelligent Positioning Plate Predictive Control and Concept of Diagnosis System Design

Session 5: Review of Classical Astrodynamics

Multivariable PID Control Design For Wastewater Systems

Transcription:

Available online at www.sciencedirect.com ScienceDirect rocedia Technology (16 ) 59 599 9th International onference Interdiscilinarity in Engineering, INTER-EN 15, 8-9 October 15, Tirg-Mres, Romania IM based ID ontrol of a Magnetic Levitation System Adrian-Vasile Da a, Mircea Dl a, Stelian-Emilian Oltean a, * a etr Maior University of Tg. Mre, No. 1 N.Iorga St., Tg.Mre, 5488, Romania Abstract Attraction tye magnetic levitation devices are nonlinear and nstable systems with fast dynamics. If a model of sch a system can be rodced, it cold be sed in the design rocess of a stabilizing controller. Internal Model ontrol (IM) rovides a strategy that exlicitly ses an existing model of the controlled rocess for develoing a sitable controller. In this aer, a linear model that reresents the nonlinear dynamics of the magnetic levitation system is first derived. Then, this model is sed in the design rocedre of an IM-based ID controller, which is sed for achieving stable levitation of a ferromagnetic object at redetermined distances with the hel of the magnetic field rodced by a coil. The reslts are shown by means of digital simlation, based on Simlin. 16 The Athors. blished by by Elsevier Ltd. Ltd. This is an oen access article nder the BY-N-ND license (htt://creativecommons.org/licenses/by-nc-nd/4./). eer-review nder resonsibility of the etr Maior University of Tirg-Mres, Faclty of Engineering. eer-review nder resonsibility of the etr Maior University of Tirg Mres, Faclty of Engineering Keywords: magnetic levitation; Internal Model ontrol; ID control. 1. Introdction Magnetic levitation is the rocess by which a ferromagnetic object is ssended in the air against gravity with the hel of a magnetic field generated by a coil. This rocess resents many ractical alications sch as: active magnetic bearings, vibration daming, ssension of wind tnnel models, transortation systems (e.g high seed assenger trains) etc. This aer investigates the develoment of a control system for a single degree of freedom magnetic levitation rocess who aims at obtaining stable levitation of a steel ball at redetermined distances, sing an IM-based ID controller. While the rincile of levitation is simle: by controlling the crrent throgh the coil an electromagnetic * orresonding athor. Tel.: +4-65-331 E-mail address: adrian.da@ing.m.ro 1-173 16 The Athors. blished by Elsevier Ltd. This is an oen access article nder the BY-N-ND license (htt://creativecommons.org/licenses/by-nc-nd/4./). eer-review nder resonsibility of the etr Maior University of Tirg Mres, Faclty of Engineering doi:1.116/j.rotcy.16.1.15

Adrian-Vasile Da et al. / rocedia Technology ( 16 ) 59 599 593 force is generated which is able to conteract the weight of a steel ball, the magnetic levitation systems (MLS) are nonlinear, nstable systems with fast dynamics. These roerties mae them good candidates as test beds for different control algorithms. Over the ast years, varios control strategies have been roosed for this tye of systems, sch as ID [,1,1], hase-lead comensation [16,19], feedbac linearization controllers [11,13,], sliding mode control [1,5], fzzy logic ID-tye controllers[9,1,1], neral networs [3] etc. In many cases, ID has roved itself to be an effective soltion in controlling these systems. It is easy to imlement, bt setting its arameters is somewhat difficlt, de to the natre of the MLS. The roblems reslt from the lant model ncertainties and the small oerating ranges of MLS. The IM control strategy is based on the fact that if a model of the controlled lant can be rodced, even if it is an aroximate one, it can be sed exlicitly in the design of the controller. For many lant models in indstry, classical ID controllers can be viewed as eqivalent arameterizations of IM controllers [14,18]. Using the IM secifications, the tning rocess of a ID controller is simlified and it is redced to changing jst one arameter, the closed loo time constant (the IM filter factor ), instead of three [4,14]. In [4,14,18] ID tye controllers are designed based on IM for different tyes of lants (first, second order, stable, nstable, dead time). For the MLS considered in this aer, first, a linear model is dedcted, which is written in the form of a second order transfer fnction with oles on both sides of the comlex lane. Then, as shown in section 3, this model is sed to design an IM-based ID controller for the lant. The effectiveness of the reslted controller is demonstrated by means of digital simlation sing Matlab/Simlin sing a nonlinear model of the lant, which was validated in [8].. lant model The mathematical model of the MLS, shown in eqation (1), is fond by alying Newton s law for the eqilibrim of forces. d x( m mg + f ( x, i, (1) e dt where: where f e (x,i, is the electromagnetic force that conteracts the weight of the ball, x( is the distance between the coil and the steel ball, i( is the crrent throgh the coil, m is the mass of the ball and g is the gravitational constant [1,19]. Fig. 1. The magnetic levitation system.

594 Adrian-Vasile Da et al. / rocedia Technology ( 16 ) 59 599 The electromagnetic force f e generated by crrent i( which flows throgh the coil is given by [7,19]: i( f e ( x, i, () x( where is a nonlinear arameter which is assmed to be constant for model simlification roses. In reality arameter deends on the levitation oint, as demonstrated in [8] and encaslates some of the system s nonlinearities which are very difficlt to model. For a given levitation distance (X ) this arameter was determined exerimentally. The linear model of the lant is determined sing system linearization abot an eqilibrim oint (I, X), where I is the crrent throgh the coil when the ball is at X, by exanding the Taylor series of () and reserving the first order terms. I I I f e ( x, i, ( ) + ( ) +... i I 3 x X (3) X X X In stationary regime, when levitation is achieved (i(i and x(x ) the electromagnetic force cancels gravity and the acceleration dx/dt, eqation (1) taes the following form [19]: I mg (4) X By combining (1),(3) and (4) we get: d xˆ I I m iˆ + xˆ (5) 3 dt X X where xˆ x X and iˆ i I. Eqation (5) reresents the linear eqation which describes the dynamic of the magnetic levitation system (lan. Based on this eqation, sing Lalace transform, we get the transfer fnction of the lant shown in eqation (6). H 1 ms Xˆ (6) Iˆ where 1 and are two constants deending on arameters, I and X. The dislacement of the steel ball arond the oerating oint X is determined sing a sensor system consisting of an infra-red LED and a hototransistor. The crrent throgh the coil is rodced with the hel of a crrent amlifier. Both the sensor and the crrent amlifier are linear elements which can be described by the roortional gain transfer fnctions K sens, K am. By considering these additional elements the following transfer fnction of the rocess is fond: ~ ' 1 1 K amk sens (7) ms ms

Adrian-Vasile Da et al. / rocedia Technology ( 16 ) 59 599 595 where 1 1 K am K sens The arameters in Table 1 characterize the rocess linearized abot the eqilibrim oint (X,I ). Table 1. MLS arameters. arameter Vale Observation m.11 g Mass of the levitated steel ball X.76 m Eqilibrim osition I.41 A Eqilibrim crrent 3.84 1-5 Nm /A onstant, corresonding to the air (X, I ) (7.6mm, 41mA). 1.4677 N/A arameter of the transfer fnction in (6) 5.987 N/m arameter of the transfer fnction in (6) K sens Arox. 3333 V/m Sensor system transfer fnction (gain) K am.1 A/V rrent amlifier transfer fnction (gain) 3. IM-based ID control of the MLS 3.1. The IM-ID eqivalence Fig..a shows the standard IM strctre. By manilating the bloc diagram, an eqivalent feedbac control strctre can be obtained (Fig..b), where the feedbac controller is given by: ~ 1 where: form of a ID controller [18]. IM IM IM is the internal model controller and ~ is the internal model. In most cases has the (8) Fig.. (a) IM strctre; (b) Eqivalent feedbac strctre.

596 Adrian-Vasile Da et al. / rocedia Technology ( 16 ) 59 599 3.. IM-based ID design for the MLS This section shows the design rocedre for a ID controller eqivalent to the IM for the MLS modeled in section. For this rose, the model of the lant of eqation (7) is rewritten in the following form: ~ ( τ s + 1)( τ s + 1) (9) where: ' / 1 is the rocess gain and τ τ m / are two ositive time constants. As seen in (9), the rocess has two oles, located on both sides of the comlex lane. s1/ reresents the nstable ole located in the right half art of the comlex lane, while s-1/ is the stable ole. The first ste in finding the ID controller is finding the internal model controller s transfer fnction IM (s), as shown in eqation (1). IM ~ 1 F() s As recommended in [4,15] this fnction incldes a low-ass filter: (1) F γs + 1 λ ( s + 1) n (11) where: n is the filter s order and is sally chosen to mae IM (s) roer or semiroer, is the filter s time constant and satisfies the filter reqirement of eqation (1). F s 1 1 τ (1) Becase we want to end with an ideal ID controller, we choose n, maing IM (s) imroer. According to [17,18] this action is allowed since IM (s) will have a zero excess of at most 1 which is needed for the ID. Solving eqation (1) for we find: λ γ λ + (13) τ In order to find the eqivalent feedbac controller, we se the transformation of eqation (8) as follows: ~ 1 IM IM 1 ( τ s + 1)( τ s + 1) γs + 1 ( λs + 1) ( τ s + 1)( τ s + 1) γs + 1 ( τ s + 1)( τ s + 1) ( λs + 1) (14) which leads to:

Adrian-Vasile Da et al. / rocedia Technology ( 16 ) 59 599 597 ( γ + τ ) γτ s + ( γ + τ ) τ s + 1 (15) λ ( γ + τ )s Recalling that the transfer fnction for a standard ID controller is: 1 TiTd s + Ti s + 1 1+ + Td s Ti s (16) Ti s we find the following relationshis for the ID arameters [4]: T T i d τ ( γ + τ ) λ γ + τ γτ γ + τ (17) As seen the ID arameters in eqation (17) deend on a single variable, the low-ass filter s time constant. 4. Simlation reslts In order to test the reslted controller, Matlab/Simlin simlations were erformed. These simlations were based on the following closed loo model of the magnetic levitation control system. Fig. 3. Schematic diagram illstrating the model sed for simlating the magnetic levitation control system sing the IM-based ID controller The arameters of Fig. 3 are: Xˆ - dislacement of the ball from the eqilibrim osition; V x sensor ott X ˆ ; V - voltage, roortional to Xˆ ; V s - setoint voltage needed to ee the ball at the desired osition sly voltage needed for I ; Vˆ - ott control voltage; I - electromagnet crrent. The ID controller reslted from the rocedre discssed in Section 3 is an ideal controller, which is imroer. The imlementation isses that it raises are addressed by considering a filter coefficient N1 for the derivative comonent, that sets the location of the ole in the derivative filter far away in left hand art of the comlex lane. Eqation (18) shows the transfer fnction of the considered ID controller. 1 T () d Ns s 1 + + (18) Ti s s + N

598 Adrian-Vasile Da et al. / rocedia Technology ( 16 ) 59 599 Since is the only tning arameter of the controller (see eqation (17) and (13)), Fig. 4.a shows the closed loo ott resonses to a ste int for different vales of. All trajectories shown in the next figres are relative to the eqilibrim osition X. Fig. 4. (a) losed loo ott resonse to a ste int for different vales of ; (b) losed loo ott resonse to a ste int for different vales of, with setoint filter. Fig.4 shows that the closed loo resonse to ste int has qite significant overshoot. This is not accetable since the levitated object cold find itself otside the range of the osition sensor. A ste resonse withot overshoot can be obtained by sing a setoint filter of the following form [4]: F s 1 γ s + 1 (19) Fig. 4.b shows the closed loo ott resonses to a ste int for different vales of, considering the setoint filter of eqation (19). By choosing.8, almost erfect set-oint tracing caabilities (no overshoot, fast resonse time) are obtained, as shown in Fig. 5. Fig. 5. losed loo ott resonse for sqare trajectory tracing (.8), with setoint filter.

Adrian-Vasile Da et al. / rocedia Technology ( 16 ) 59 599 599 5. onclsion This aer showed the design rocedre of an IM-based ID controller for a nonlinear nstable rocess. For the MLS sed in this aer, a second order linear model was fond that had one nstable ole. Using this model as internal model, by following the rocedre described in Section 3 and in [4], an ideal ID controller was determined for the rocess. The reslting controller had the advantage that its tning arameters ( c, T i, T d ) had an analytical reresentation which deended on model s arameters and on a single variable arameter (), which became the controller tning arameter. This simlified the tning rocess. The reslts in Section 4 show the closed loo system resonse to a ste change for varios vales of. By sing a standard choice as setoint filter the system s resonse is imroved and the initial overshoot is eliminated. hoosing a convenient vale for reslts in a damed resonse with short settling time, which is sitable for the limited oerating range of the osition sensor, bt also for assring erfect setoint tracing caabilities. References [1] Al-Mthair NF, Zribi M. Sliding Mode ontrol of a Magnetic Levitation System. Mathematical roblems in Engineering, no.,.93 17, 4 [] Ahmad I, Shahzad M, alensy. Otimal ID control of Magnetic Levitation System sing enetic Algorithm. Energy onference (ENERYON), 14 IEEE International, vol., no.,.149-1433, 13-16 May 14 [3] Aliasghary M et al. Sliding Mode ontrol of Magnetic Levitation System Using Radial Basis Fnction Neral Networs. Robotics, Atomation and Mechatronics, 8 IEEE onference on, vol., no.,.467-47, 1-4 Set. 8 [4] Beqette BW. rocess ontrol: Modeling, Design, and Simlation. rentice Hall rofessional, hater 9,. 85-313, 3 [5] Bethox O, Floqet T, Barbot J. Advanced sliding mode stabilization of a Levitation system. Eroean ontrol onference (E), 3, vol., no.,.51-56, 1-4 Set. 3 [6] De-Sheng Li, Jie Li, Wen-Sen hang. Internal Model ontrol for Magnetic Ssension System. Machine Learning and ybernetics, 5. roceedings of 5 International onference on, vol.1, no.,.48-487, 18-1 Ag. 5 [7] Dolga V, Dolga L. Modelling and Simlation of a Magnetic Levitation System, Annals of the Oradea University, Fascicle of Management and Technological Engineering, vol. VI (XVI),.1118 114, 7 [8] Da AV. Modelling of an electromagnetic levitation system sing a neral networ, 1 IEEE International onference on Atomation, Qality and Testing Robotics (AQTR1), vol. I,.79-83, May 1 [9] olob M, Tovorni B. Modeling and control of the magnetic ssension system. ISA Transactions, vol. 4, isse 1,. 89 1, Jan. 3 [1] o QH, et al. Research on a Maglev Ball ontrol System Based on DS81, rogress In Electromagnetics Research Symosim (IERS) roceedings,. 536-539, 4-8 Mar. 8 [11] Ishtiaq Ahmad, Mhammad Aram Javaid. Nonlinear model & controller design for magnetic levitation system. ISRA'1 roceedings of the 9th WSEAS international conference on Signal rocessing, robotics and atomation,. 34-38, 1 [1 ]Jie Ma, Wenjn Fan, Fengha He. arameters self-adjsting fzzy ID control in magnetic levitation system. Systems and ontrol in Aerosace and Astronatics, 8. ISSAA 8. nd International Symosim on, vol., no.,.1-5, 1-1 Dec. 8 [13 ]Kmar T, et al. Modeling, simlation and control of single actator magnetic levitation system. Engineering and omtational Sciences (RAES), 14 Recent Advances in, vol., no.,.1-6, 6-8 Mar. 14 [14] Morari M, et al. Imlications of Internal Model ontrol for ID ontrollers American ontrol onference, vol., no.,.661-666, 1984 [15] Morari M, Zafirio E. Robst rocess ontrol, rentice-hall, 1989 [16] Namovi MB, Veseli BR. Magnetic Levitation System in ontrol Engineering Edcation, FATA UNIVERSITATIS Series: Atomatic ontrol and Robotics, vol.7, no.1,. 151 16, 8 [17] Rivera DE. Internal Model ontrol: A comrehensive view. Technical reort, Deartment of hemical, Bio and Materials Engineering, ollege of Engineering and Alied Sciences, Arizona State University, 1999. [18] Rivera DE, Morari M, Sogestad S. Internal Model ontrol. 4. ID controller design. Ind. Eng. hem. Des. Dev., 5:5-65, 1986 [19] Shiao YS. Design and Imlementation of a ontroller for a Magnetic Levitation System. roc. Natl. Sci. onc. vol. 11 no.,. 88-94, 1. [] Bhawna Tandon et al. Exlicit Feedbac Linearization of Magnetic Levitation System. World Academy of Science, Engineering and Technology, International Jornal of omter, ontrol, Qantm and Information Engineering, vol. 8, no. 1,. 1738-1748, 14 [1] Yadav S, Tiwari J, Nagar SK. Digital ontrol of Magnetic Levitation System sing Fzzy Logic ontroller. International Jornal of omter Alications, vol.41, no.1,. -6, Mar. 1