PERFORMANCE REQUIREMENTS AND CRITERIA

FBW/FCS should achieve (1) performance robustness in spite of uncertainty in plant, i. e., aircraft dynamics, and in the presence of external disturbance and (2) good command following. The FCS/control laws should also provide sufficient gain and phase margins (Appendix C) and adequate gains roll-off at high frequencies so that noise, aircraft model uncertainties, and structural modes have negligible effects on the flight/mission performance of the aircraft [5]. In most cases of design and development of a flight vehicle, especially manned aircraft, the specifications of the required handling qualities are incorporated in the design cycle. This is more so for the design of flight control laws. The time-domain and frequency-domain criteria are specified for handling qualities evaluation of the pilot-aircraft interactions (Chapter 10). At times these requirements would be conflicting in nature and some engineer­ing judgment and insights are needed to arrive at an acceptable and satisfactory design and to meet the desired goals.

8.2 PROCEDURE FOR THE DESIGN AND EVALUATION OF CONTROL LAWS

The design of flight control laws is a multidisciplinary process in which aerody­namic, structural, propulsive, and control functions are considered together. Modern flight controllers may excite structural modes of the aircraft. These modes would interact with the control-actuator dynamics. Also, because of the increasing need to integrate flight controls with engine controls, the interactions between aerodynamics, propulsive, and structural modes should be investigated and taken into account. Due to extensive use of composite (material) in the design of the airframe and control surfaces, aeroelastic coupling would also play a significant role in the design process of flight control laws.

Design and development of an FBW/FCS and autopilot presuppose a good understanding of the dynamics of the aircraft and easy availability of the mathematical models of these dynamics over the entire flight envelope (Chapters 2 through 5). Primarily, such information is available in the form of an aero database (Chapter 6),
which is usually in the form of lookup tables. These tables are constructed based on the extensive wind tunnel tests carried out on scaled (down) models of the aircraft during the design/development cycles. The database would be in terms of aerodynamic coefficients as function of several independent variables: Mach number, alpha, control surface deflection, store configurations, and any such parameter that would have major or moderate effect on these coefficients. That is, at a given flight condition (altitude, Mach number) and with the specification of other relevant parameters, one should be able to determine the values of these aerodynamic coefficients. These coefficients are used in the EOM to obtain the flight responses as discussed in Chapter 6.

A very close scrutiny of this aero database is made and the flight mechanics parameters are computed (Chapter 4) [5]. These are in terms of aerodynamic (or stability and control) derivatives and other compound derivatives; for example, the maximum roll rate is given as pmax = — 8a 2V. In a combat flight phase operation

the aircraft would have a large roll rate/However, a desired value might not be available due to limited control power and limits on the structure. In fact, dimensional linear models (Chapter 5) are obtained at several flight conditions and configurations. These models and the design specifications form a starting point for the design of control laws for the given aircraft. The design specifications could be: (1) frequency domain parameters or (2) time-domain parameters. These performance indices are collected and put in a vector form and called vector performance index, which is to be optimized. Often the structures of controller blocks (called controller transfer func­tions or filters) are specified. At times, various criteria could be of conflicting nature, and hence, some relaxation/compromise would be required in the performance of the designed system. Also, certain required constraints on the controller gains, actual control gains, and time constants (Chapter 2, Appendix C) could be specified so that these gains are not unrealizable. This process is the multi-input multi-output (MIMO) pareto-optimal or conditionally optimal control-law design procedure. In an inter­active design process, the control design engineer also simultaneously looks at the dynamic responses of the closed loop systems for checking the limits and the shape of the responses for guidance in the design process. The entire design process can be almost fully automated, thereby freeing the designer from the tedious design cycles and iterations. This is a very practical design procedure for the determination of flight control laws and can form a substantial part of the rapid prototyping formulation and computational paradigm. Hence, in general, the procedure centers around: (1) avail­ability of all the subsystem models that form the entire aircraft closed loop system, such as actuators, sensor, anti-aliasing filters, ADC/DACs, quantization errors, and computational delays (Chapter 6), (2) controller structures, and (3) closed loop system performance criteria, such as stability margins and conventional control system criteria. The computational delays can be modeled by a second-order lag TF. Often first-order TF of the form (K/(K + s)) would suffice as a model for the actuator. Controller structure could be in the form of a state space or TF. Subsystem modeling and modeling of aircraft from aero database are discussed in Chapter 6.

Subsequently, the handling qualities are evaluated and full nonlinear flight simulation (FS) is carried out. Invariably the FS is used in the flight control design cycle iterations wherein an engineer (in-the loop) would fly the simulator and perform several different types of maneuvers and failure modes and give the

assessment of the performance of the closed loop control system (aircraft and controllers). Other stages of evaluation of control laws are the following: (1) real­time simulator, (2) iron bird (and HILS-hardware in loop simulator), and (3) in-flight simulator (IFS) (Chapter 6). A comprehensive and iterative procedure [5,6] for the design of a flight-control system is depicted in Figure 8.2.

Example 8.3

The simplified block diagram of a flight-control system of a high-performance fighter aircraft is given in Figure 6.11. Use the MATLAB/SIMULINK tool to realize the interconnected blocks (Example 6.2) and vary the “destabilizing’’ gain and study the effects on the output responses.

Solution

To find the destabilizing gain, one can change each gain value individually keeping other gains invariant. From the various simulation studies (ExampleSolSW/Example8.3Control – Simu), the gain k6 is spotted as a destabilizing gain. If k6 is increased, system response becomes destabilizing, which can be seen in Figure 8.3. The simulation study is carried out with the gain k6 = 5 and all other gains are kept unaltered.