Efficient control law analysis and design tools which properly account for the interaction of flexible structures, unsteady aerodynamics and active controls are developed. Development, application, validation and documentation of efficient multidisciplinary computer programs for analysis and design of active control laws are also discussed

Adams, W. M., Jr.

Newsom, J. R.

Tiffany, S. H.

English

NASA Technical Reports Server

TOOLS FOR ACTIVE CONTROL SISTEM DESIGN 
William M. Adams, Jr., Sherwood H. Tiffany, 
and Jerry R. Newsom 
NASA Langley Research Center 
Hampton, Virginia 
First Annual NASA AirSraft Controls Workshop 
NASA Langley Research Center 
Hampton, Virginia 
October 25-27, 1983 
263 
https://ntrs.nasa.gov/search.jsp?R=19840012514 2020-03-22T08:13:25+00:00Z
The objective of the research reported here is to develop efficient control law 
analysis and design tools which properly account for the interaction of flexible 
structures, unsteady aerodynamics and active controls. The next two figures indicate 
how such tools can be employed to incorporate active controls into the aircraft 
design process. 
DEVELOPMENT. APPLICATION. VALIDATION AND DOCUMENTATION OF 
EFFICIENT MULTIDISCIPLINARY COMPUTER PROGRAMS FOR ANALYSIS 
AND DESIGN OF ACTIVE CONTROL LAWS 
264 
UTOPIAN DESIGN PROCESS 
The optimum airplane for a given mission can only be achieved when full advan- 
tage is taken of the economic and/or performance benefits that are achievable from 
each discipline. One could argue that these benefits can best be realized when the 
design variables from each discipline are varied simultaneously in the search for an 
optimum design. Currently, however, the process is to perform the optimization sepa- 
rately, but not independently, in each discipline. A given discipline, e.g. aerody- 
namics, may relax certain design criteria and assume that other disciplines, e.g. 
structures and controls, can make up deficits in stability, safety margins, etc., 
that result. 
INITIAL - 
CUNFIGURATIOI 
MULTIDISCIPLINAKY 
ANALYSIS 
CR 
-STRUCTURES 
-AERODYNAMICS 
-CONTROLS 
-PROPULSION 
I ERIA 
T 
] PEKFO;hANCE 6 YEq-iiii-& 
OPTIMIZER 
KKl 
VARIABLES 
NO 
\I 
I 
265 
PRESENT CONTROL LAW DESIGN PROCESS 
The following diagram illustrates the current active control law design 
process. Fixed models are received from the structures and aerodynamic disciplines. 
These models may have been purposely designed with deficits in stability, strength 
and flutter margins. The controls specialists initially determine an estimate of the 
control law that is required to remove the deficits. An iterative process is then 
initiated to refine the control law to remove the deficits while satisfying robust- 
ness, control power and other criteria. If the design criteria cannot be met, or if 
they can easily be satisfied, the other disciplines repeat their portion of the 
design process with appropriately modified design criteria and supply the controls 
discipline with updated models. This process is repeated until it converges upon an 
optimum design. The remainder of the paper will describe techniques for obtaining 
initial estimates of the control laws, performing aeroelastic analyses and optimizing 
the control laws subject to specified design criteria. 
CRITERIA 
FIXED 
AlRFRAfiE \ / tLASl IL 
ESTIMATE ANALYSIS 
OF CONTROL 
YES 
fN0 V 
266 
ANALYSIS TOOLS 
Efficient tools for the analysis of stability and response characteristics of 
aeroelastic vehicles are necessary before active control law design can be contem- 
plated. Such tools must properly consider the interactions between flexible struc- 
tures, unsteady aerodynamics and active control systems. Several computer programs 
were developed in the 1970's either by NASA or under NASA sponsorship. DYLOFLEX is 
an integrated system of stand-alone computer programs whichwas developed primarily to 
perform dynamic loads analyses of flexible airplanes with active controls (ref. 1); 
it also has stability analysis capability. DYLOFLEX was developed under contract by 
the Boeing Company and is available from COSMIC (Computer Software Management and 
Information Center). Several years ago an aeroelastic capability was incorporated 
into NASTBAN by the MacNeal-Schwendler Corporation (ref. 2). This addition gave 
NASTRAN the capability to compute unsteady aerodynamic forces and stability and dyna- 
mic response characteristics of aeroelastic vehicles with active controls. NASTRAN 
is available from COSMIC. The aerodynamic forces are expressed in transcendental 
form in both DYLOFLEX and NASTBAN. Consequently, the equations of motion are not in 
a form that can be used in linear system analysis. One final tool, ISAC, developed 
at Langley (ref. 3) is described in more detail on the next chart. 
o DYLOFLEX DYNAMIC LOADS OF FLEXIBLE 
STRUCTURES WITH ACTIVE 
CONTROLS 
o NASTRAN NASA STRUCTURAL ANALYSIS 
PROGRAM 
o ISAC INTERACTION OF STRUCTURES 
AERODYNAMICS AND CONTROLS 
267 
ISAC 
Flexible structures are represented in ISAC in terms of a modal characterization 
that is input from an external source such as NASTRAN. Unsteady aerodynamic forces 
can be either accepted as input or computed internally using a doublet lattice code 
(ref. 4). An option is included to make a rational s-plane approximation to the 
unsteady aerodynamic forces (ref. 5). This allows the equations of motion to be 
written in time-invariant state space form amenable to linear systems analysis and 
design techniques (refs. 5,6). Stability and dynamic response calculations can be 
made and displayed graphically that include the effects of sensor dynamics, actuator 
dynamics and multi-input/multi-output control laws. The ISAC program is operable in 
either a batch or an interactive mode. Its use is greatly facilitated by the pre- 
sence of a data complex and data complex manager for reading, writing, storing, and 
cataloging of data. The ISAC program is regularly used in NASA Langley-related 
research. It is partially documented and has been distributed to several users 
outside Langley. 
I 
I ,Icm\ MODE SHAFE I 
MODAL SELECT. 
INTERPOLATIONS 
DEFLECTIONS J 
268 
DAST ARW-2 PROJECT SUPPORT 
The ISAC program is being used to support the DAST (Drones for Aerodynamic and 
Structural Testing) ARW-2 (Aeroelastic Research Wing Number 2) project. The ARW-2, 
scheduled for flight tests in calendar year 1985, is dependent upon several active 
control functions for safety of flight in some regions of its flight envelope. Ini- 
tial support involved comparison of NASA and Boeing Wichita analytic predictions of 
stability and response characteristics. These comparisons were valuable in that they 
pointed out the need for modeling improvements in both ISAC and the Boeing Wichita 
programs. The NASA/Boeing predictions are now in reasonably good agreement although 
differences remain in predicted gain and phase margins in the flutter suppression 
control law. Ultimately, the correlation of measured and analytically predicted 
performance will be documented. These comparisons will, hopefully, provide informa- 
tion that will help to improve current mathematical modeling techniques. Reference 7 
in these workshop proceedings presents the results of several experimental tests 
involving active controls for which analytical modeling and prediction of control law 
performance were done in part using ISAC. This chart also depicts some of the graph- 
ical outputs that can be obtained by use of ISAC. 
0 COMPARBON OF NASA AND BDEINQ PREWCTIOM OF DAST 
ANW-2 STAEJUTY AND RES#)IYSE CHhRACEmSlWS 
269 
DESIGN TOOLS 
A number of control law design tools have been developed at Langley: 
ORACLS (ref. 8) is a system of algorithms for designing linear feedback control laws 
for linear time-invariant multivariable differential or difference equation state 
vector models. ORACLS applies some of the most efficient numerical linear algebra 
procedures to implement Linear Quadratic Gaussian (LQG) methodology. The ORACLS 
system can be obtained from COSMIC. 
MICAD (refs. 9-11) uses goal-oriented strategies to obtain pareto-optimal solutions 
that satisfy multiple objectives for either deterministic plants or plants with ran- 
dom parameters. MICAD is, to some degree, a special purpose tool that was developed 
to design control laws for the lateral degrees of freedom of rigid aircraft. It is, 
nevertheless, generalizable to a wider class of problems. Documentation of MICAD is 
planned but a completion date has not been identified. A. A. Schy is directing the 
development of MICAD. Since the 1960's he has advocated the explicit inclusion of 
design criteria in the design process. 
PADLOCS (refs. 12-14) and SYNPAC (refs. 15,16) are two collections of algorithms 
which provide the capability to design implementable low order active control laws 
for high order aeroelastic aircraft. They allow direct inclusion of design criteria 
and, consequently, are similar in structure to MICAD. The three programs do, hop 
ever, differ substantially internally in performance function and constraint formula- 
tions and in options for obtaining constrained optimization solutions. Documentation 
of SYNPAC is now in progress. 
o ORACLS UPTIRAL REGULATOR ALGORITHMS 
FOR THE CONTROL OF LINEAR 
SYSTEMS 
o HICAD MULTIOBJECTIVE INSENSITIVE 
COMPUTER AIDED DESIGN 
o PADLOCS PROGRAMS FUR ANALYSIS AND 
DESIGN OF LINEAR OPTIMAL 
CONTROL SYSTEMS 
o SYNPAC SYNTHESIS PACKAGE FOR ACTIVE 
CONTROLS 
270 
ISAC/ORACLS/SYNPAC INTERFACE 
An approach to control law design commonly employed at Langley in active control 
applications is illustrated using the ISAC, ORACLS and SYNPAC programs. A model of 
the plant is defined using ISAC and stored on the data complex. TRANSFR, a module of 
SYNPAC, is used to examine pole-zero locations associated with candidate feedback 
paths and to prepare input to an interactive version of ORACLS. These input data 
include the model of the plant and estimates of the intensities of noise sources in 
the plant and in the sensor outputs. Full order controllers are designed using 
ORACLS. The Doyle-Stein (ref. 17) procedure of adding fictitious process noise at 
the input is employed where necessary to improve the robustness characteristics of 
the full order controller. Modal residualization/truncation is employed to select an 
implementable reduced order controller. Within SYNPAC, or other similar design 
algorithms, the reduced order controller is optimized as shown in the next chart. 
LQG 
DESIGN 
SELECT 
HHW&D- 
CONTROLLER 
271 
SYNTHESIS PACKAGE FOR ACTIVE CONTROLS 
This chart illustrates the phase of the design cycle initiated after a candidate 
control law form has been selected. The selection process has been illustrated on 
the previous page for the modified LQG approach. Other techniques could have been 
employed to select the control law form such as Nissim's energy method (ref. 18), 
eigenspace methods (refs. 19 and 20), classical methods, etc. Constrained optimiza- 
tion techniques are employed to determine values for the free parameters in the fixed 
form control law which optimize a measure of goodness and allow the design criteria 
to be satisfied. 
DESIGN FEEDBACK GAINS DESIGN 
VARIABLES FILTER COEFFICIENTS CONSTANTS DESIGN POINTS 
\ SENSOR LOCATIONS < CONTROL LAW FORM 
y ETC. ETC. 
Y 1 
PERFORMANCE -
FUNCTION -ANALYSl 
t 
MODULE 
--7 
LOAD I 
CONTROL [ ” 
POWER 
-- 
t l-c. 7 
CONTROL POWER 
LOADS 
DAMPING RATIOS 
ETC. 
272 
SENSOR SIGNAL IPUTS TO SYMMETRIC FLUTTER SUPPRESSION CONTROL LAW 
This and the next three charts show the application of SYNPAC to improve the 
robustness characteristics of a control law for suppression of symmetric flutter of 
the DAST ARW-2 aircraft. A more complete description is presented in reference 16. 
This chart depicts the. sensors (vertical accelerometers) and control surfaces that 
were employed and defines how the sensor signals are separated into symmetric compo- 
nents. Note that the control law is single-input/single-output. 
ACCELEROMETERS 
2 PER SEMISPAN 
AILERON 
RIGHT 
WING 
COMMAND 
> SYMMETRIC CONTROL AW 'AILERON 
TO 
ACTUATOR 
273 
ROBUSTNESS MAXIMIZATION 
In reference 16 a full order controller (25th order) was designed using ORACl,S 
for a design point at a Mach number of 0.86 and an altitude of 15,000 ft. Order 
reduction techniques were used to obtain an implementable 9th order approximation to 
this controller of the form indicated below. The controller exhibited poor robust- 
ness characteristics at an off design point at a Mach number of 0.91 and an altitude 
of 15,000 ft. SYNPAC was employed to improve the robustness characteristics. Design 
variables Di (i=1,2 ,...,9) were found which maximized the minimum singular value of 
the return difference transfer function subject to the indicated constraints. 
FIND VALUES FOR THE DESIGN VARIABLES. DI. 
2 
( s+D2) h+Dj) ( s +D6S+D7) 
hl /Y) = D 
---------me- ---_---____ 
FS 12 2 
( s +D4s+D51 (s +D8S+D9) 
AND T(S) IS A FIXED FILTER 
SUCH THAT 
WHERE 
T(s) 
0 MINIMUM SINGULAR VALUE IS MAXIMIZED 
0 CONTROL POWER CONSTRAINTS ARE SATISFIED 
0 +6DB < GAIN MARGIN < -6DB 
0 40' s PHASE MARGIN s -40' 
274 
CLOSED MOP BLOCK DIAGRAM 
The performance of the controller optimized for robustness will be exhibited by 
showing Nyquist plots for the initial and optimized controllers. This chart identi- 
fies the loop breaking point and symbols employed to represent the pertinent transfer 
functions. 
I I 
INPUT >o ' OUTPUT UR ?- " 1:; 
275 
NYQUIST PLOTS OF HG TRANSFEH FUNCTION 
(M = 0.91, H = 15,000 FEET) 
The plant is unstable (a complex conjugate pair of unstable poles) at the indi- 
cated flight condition. Consequently, for stability the Nyquist plot must encircle 
the (-1) point once' in a counterclockwise direction as frequency varies from 0 to 
+-co. Increasing frequency is indicated by arrows on the figure. The initial control- 
ler stabilized the system but exhibited poor gain and phase margins with an accom- 
panying small minimum singular value (the point at which the minimum singular values 
occurs is indicated by the heavy solid line). After optimization the minimum singu- 
lar value was increased by 26 percent, control power constraints (not shown) were 
satisfied and gain and phase margin constraints ware met to within a 2.5-percent 
tolerance. 
lmoginary 
INITIAL CONTROLLER 
Imoghmy 
OPTIMIZED CONTROLLER 
276 
CONCLUDING REMARK3 
Several tools applicable to analysis and design of control laws for aeroelastic 
vehicles have been identified. DYLOFLEX and NASTRAN are available from COSMIC. 
ISAC, developed primarily for in-house research, is only partially documented and 
would require substantial modification for use on a computer complex differing from 
the one at Langley. It has, nevertheless, been distributed to several off-site 
users. ORACLS is the only design tool that is sufficiently well documented for dis- 
tribution. Linear potential flow aerodynamic theory is employed in computing aerody- 
namic forces. Consequently, the modeling accuracy becomes doubtful at analysis and 
design points approaching the transonic region. Improvement is needed in the aerody- 
namic modeling. 
l ANALYSlS AND DESIGN TOOLS IDENTIFIED 
l CKITERIA EXPLICIlLY INCLUUED IN DESIGN PROCEUUHE 
l CONCERN ABOUT UNMODELED NONLINEAR AERODYNAMIC EFFECTS 
l DOCUMENTATION OF ANALYSIS AND DESIGN TOOLS IS UNDERWAY 
277 
REFERENCES 
1. Perry, B. III; Kroll, R. I.; Miller, R. D.; and Goetz, R. C.: DYLOFLEX: A 
Computer Program for Flexible Aircraft Flight Dynamic Loads Analysis with Active 
Controls. Journal of Aircraft, Vol. 17, No. 4, April 1980, pp. 275-282. 
2. Harder, Robert L.; MacNeal, Richard H.; and Rodden, William P.: A Design Study 
for the Incorporation of Aeroelastic Capability into NASTRAN. NASA CR 111918, 
May 1971. 
3. Peele, Ellwood L.; and Adams, William M., Jr.: A Digital Program for Calculat- 
ing the Interaction Between Flexible Structures, Unsteady Aerodynamics, and 
Active Controls. NASA TM 80040, January 1979. 
4. Albano, E.; and Rodden, W. P.: A Doublet Lattice Method for Calculating Lift 
Distributions on OscilLating Surfaces in Subsonic Flows. AIAA Journal, Vol. 7, 
No. 2, February 1969, pp. 279-285. 
5. Roger, Kenneth L.: Airplane Math Modeling Methods for Active Control Design. 
AGARD CR 228, August 1977. 
6. Mahesh, J. K.; Stone, C. R.; Garrard, W. L.; and Hausman, P. D.: Active Flutter 
Control for Flexible Vehicles. NASA CR 159160, November 1979. 
7. Newsom, Jerry R.; and Abel, Irving: Experiences With the Design and Implementa- 
tion of Flutter Suppressiun Systems. NASA Aircraft Controls Research - 1983, 
NASA CP-2296, 1984, pp. 489-509. 
8. Armstrong, Ernest S.: ORACLS - A Design System for Linear Multivariable 
Control. Marcel Dekker, Inc., c.1980. 
9. Schy, Albert A.: Nonlinear Programming in Design of Control Systems with Speci- 
fied Handling Qualities. Proceedings of 1972 IEEE Conference on Decision and 
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10. Schy, A. A.; Adams, William M., Jr.; and Johnson, K. G.: Computer-Aided Design 
of Control Systems to Meet Many Requirements. NATO AGARD ConEerence Proceedings 
No. 137 on Advances in Control Systems, May 1974, pp 6-l to 6-7. 
11. Schy, A. A.; and Giesy, D. P.: Tradeoff Studies in Multiobjective Insensitive 
Design of Airplane Control Systems. AIAA Paper No. 83-2273, August 1983. 
12. Newsom, J. R.: A Method for Obtainiug Practical Flutter Control Laws Using 
Results of Optimal Control Theory. NASA TP 1471, August 1979. 
13. Mukhopadhyay, V.; Newsom, J. R.; and Abel, I.: A Method for Obtaining Reduced 
Order Control Laws for High Order Systems Using Optimization Techniques. NASA 
TP 1876, 1981. 
14. Newsom, Jerry R.; and Mukhopadhyay, V.: The Use of Singular Value Gradients and 
Optimization Techniques to Design Robust ControLlers for Multiloop Systems. 
AIAA Paper No. 83-2191, August 1983. 
278 
15. Adams, William M., Jr.: and Tiffany, Sherwood H.: Control Law Design to Meet 
Constraints Using SYNPAC--Synthesis Package for Active Controls. NASA TM 83264, 
January 1982. 
16. Adams, William M., Jr.; and Tiffany, Sherwood, H.: Design of a Candidate 
Flutter Suppression Control Law for DAST ARW-2. AIAA Paper No. 83-2221, August 
1983. 
17. Doyle, J. C.; and Stein, G.: Robustness with Observers. IEEE Transactions on 
Automatic Control, Vol. AC-24, No. 4, August 1979, pp. 607-611. 
18. Nissim, E.; and Abel, I.: Development and Application of an Optimization Proce- 
dure for Flutter Suppression Using the Aerodynamic Energy Concept. NASA 
TP 1137, February 1978. 
19. Garrard, William L.; and Liebst, Bradley S.: Active Flutter Suppression Using 
Eigenspace and Linear Quadratic Design Techniques. AIAA Paper No. 2222, August 
1983. 
20. Ostroff, A. J.; and Pines, S.: Application of Modal Control to Wing-Flutter 
Suppression. NASA TP 1983, May 1982. 
279 


Tools for active control system design

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