1,869 research outputs found

    YF-12 cooperative airframe/propulsion control system program, volume 1

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    Several YF-12C airplane analog control systems were converted to a digital system. Included were the air data computer, autopilot, inlet control system, and autothrottle systems. This conversion was performed to allow assessment of digital technology applications to supersonic cruise aircraft. The digital system was composed of a digital computer and specialized interface unit. A large scale mathematical simulation of the airplane was used for integration testing and software checkout

    Evolutionary design of a full-envelope full-authority flight control system for an unstable high-performance aircraft

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    The use of an evolutionary algorithm in the framework of H1 control theory is being considered as a means for synthesizing controller gains that minimize a weighted combination of the infinite norm of the sensitivity function (for disturbance attenuation requirements) and complementary sensitivity function (for robust stability requirements) at the same time. The case study deals with a complete full-authority longitudinal control system for an unstable high-performance jet aircraft featuring (i) a stability and control augmentation system and (ii) autopilot functions (speed and altitude hold). Constraints on closed-loop response are enforced, that representing typical requirements on airplane handling qualities, that makes the control law synthesis process more demanding. Gain scheduling is required, in order to obtain satisfactory performance over the whole flight envelope, so that the synthesis is performed at different reference trim conditions, for several values of the dynamic pressure, used as the scheduling parameter. Nonetheless, the dynamic behaviour of the aircraft may exhibit significant variations when flying at different altitudes, even for the same value of the dynamic pressure, so that a trade-off is required between different feasible controllers synthesized at different altitudes for a given equivalent airspeed. A multiobjective search is thus considered for the determination of the best suited solution to be introduced in the scheduling of the control law. The obtained results are then tested on a longitudinal non-linear model of the aircraft

    Robust scheduled control of longitudinal flight with handling quality satisfaction

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    Classic flight control systems are still widely used in the industry because of acquired experience and good understanding of their structure. Nevertheless, with more stringent constraints, it becomes difficult to easily fulfil all the criteria with these classic control laws. On the other hand, modern methods can handle many constraints but fail to produce low order controllers. The following methodology proposed in this paper addresses both classic and modern flight control issues, to offer a solution that leverages the strengths of both approaches. First, an Hโˆž synthesis is performed in order to get controllers which satisfy handling qualities and are robust withrespect to mass and centre of gravity variations. These controllers are then reduced and structured by using robust modal control techniques. In conclusion, a self-scheduling technique is described that will schedule these controllers over the entire flight envelope

    Results from flight and simulator studies of a Mach 3 cruise longitudinal autopilot

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    At Mach numbers of approximately 3.0 and altitudes greater than 21,300 meters, the original altitude and Mach hold modes of the YF-12 autopilot produced aircraft excursions that were erratic or divergent, or both. Flight data analysis and simulator studies showed that the sensitivity of the static pressure port to angle of attack had a detrimental effect on the performance of the altitude and Mach hold modes. Good altitude hold performance was obtained when a high passed pitch rate feedback was added to compensate for angle of attack sensitivity and the altitude error and integral altitude gains were reduced. Good Mach hold performance was obtained when the angle of attack sensitivity was removed; however, the ride qualities remained poor

    Foreign technology summary of flight crucial flight control systems

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    A survey of foreign technology in flight crucial flight controls is being conducted to provide a data base for planning future research and technology programs. Only Free World countries were surveyed, and the primary emphasis was on Western Europe because that is where the most advanced technology resides. The survey includes major contemporary systems on operational aircraft, R&D flight programs, advanced aircraft developments, and major research and technology programs. The information was collected from open literature, personal communications, and a tour of several companies, government organizations, and research laboratories in the United Kingdom, France, and the Federal Republic of Germany. A summary of the survey results to date is presented

    Design of integrated pitch axis for autopilot/autothrottle and integrated lateral axis for autopilot/yaw damper for NASA TSRV airplane using integral LQG methodology

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    Two designs are presented for control systems for the NASA Transport System Research Vehicle (TSRV) using integral Linear Quadratic Gaussian (LQG) methodology. The first is an integrated longitudinal autopilot/autothrottle design and the second design is an integrated lateral autopilot/yaw damper/sideslip controller design. It is shown that a systematic top-down approach to a complex design problem combined with proper application of modern control synthesis techniques yields a satisfactory solution in a reasonable period of time

    Development and flight test results of an autothrottle control system at Mach 3 cruise

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    Flight test results obtained with the original Mach hold autopilot designed the YF-12C airplane which uses elevator control and a newly developed Mach hold system having an autothrottle integrated with an altitude hold autopilot system are presented. The autothrottle tests demonstrate good speed control at high Mach numbers and high altitudes while simultaneously maintaining control over altitude and good ride qualities. The autothrottle system was designed to control either Mach number or knots equivalent airspeed (KEAS). Excellent control of Mach number or KEAS was obtained with the autothrottle system when combined with altitude hold. Ride qualities were significantly better than with the conventional Mach hold system

    Flight control systems development and flight test experience with the HiMAT research vehicles

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    Two highly maneuverable aircraft technology (HiMAT) remotely piloted vehicles were flown a total of 26 flights. These subscale vehicles were of advanced aerodynamic configuration with advanced technology concepts such as composite and metallic structures, digital integrated propulsion control, and ground (primary) and airborne (backup) relaxed static stability, digital fly-by-wire control systems. Extensive systems development, checkout, and flight qualification were required to conduct the flight test program. The design maneuver goal was to achieve a sustained 8-g turn at Mach 0.9 at an altitude of 25,000 feet. This goal was achieved, along with the acquisition of high-quality flight data at subsonic and supersonic Mach numbers. Control systems were modified in a variety of ways using the flight-determined aerodynamic characteristics. The HiMAT program was successfully completed with approximately 11 hours of total flight time

    ๋น„๋Œ€์นญ ๊ฐ€๋ณ€์ŠคํŒฌ ๋ชจํ•‘ ๋ฌด์ธ ํ•ญ๊ณต๊ธฐ์˜ ์ž์ฒด์Šค์ผ€์ค„ ํŒŒ๋ผ๋ฏธํ„ฐ ๊ฐ€๋ณ€ ์ œ์–ด

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2023. 2. ๊น€์œ ๋‹จ.In this dissertation, a novel framework for flight control of a morphing unmanned aerial vehicle (UAV) is proposed. The proposed method uses asymmetric span morphing for lateral-directional motion control considering the dynamic characteristics of the morphing actuators while exploiting the advantages of symmetric span morphing for longitudinal flight performance enhancement. The proposed control system is self-scheduled based on linear parameter-varying (LPV) methods, which guarantees stability and performance for the variations of the morphing configuration and the flight condition. Therefore, the morphing UAV is allowed to swiftly metamorphose into the optimal configuration to maximize the system-level benefit according to the maneuvering command and the flight condition. First, a high-fidelity nonlinear model of an asymmetric variable-span morphing UAV is obtained from the NASA generic transport model. The impacts of morphing on the center of mass, inertia matrix, and aerodynamic coefficients are modeled based on the asymmetrically damaged wing model. The span variation ratios of the left and right wings are decomposed into symmetric and asymmetric morphing parameters, which are considered as the scheduling parameter and the control input, respectively. The nonlinear model is decoupled and linearized to obtain point-wise linear time-invariant (LTI) models for the longitudinal and lateral-directional motions throughout the grid points over the entire rectangularized scheduling parameter domain. The LPV model of the morphing UAV is derived for the longitudinal and lateral-directional motions by associating the family of LTI models through interpolation. Second, the longitudinal and lateral-directional control augmentation systems are designed based on LPV methods to track the normal acceleration command and the angle of sideslip and the roll rate commands, respectively. The inherent dynamic characteristics of the morphing actuator, such as low bandwidth, are considered in the control design procedure through a frequency-dependent weighting filter. The span morphing strategy to assist the intended maneuver is studied considering the impacts of morphing on various aspects. Numerical simulations are performed to demonstrate the effectiveness of the proposed control scheme for pushover-pullup maneuver and high-g turn. Finally, the longitudinal and lateral-directional autopilots are designed based on LPV methods to track the airspeed and altitude commands and the angle of sideslip and roll angle commands, respectively. A nonlinear guidance law is coupled with the autopilots to enable three-dimensional trajectory tracking. Numerical simulation results for the trajectory-tracking flight show that the proposed controller shows satisfactory performance, while the closed-loop system using the conventional gain-scheduled controller may lose stability when the scheduling parameter varies rapidly or widely.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ชจํ•‘ ๋ฌด์ธ ํ•ญ๊ณต๊ธฐ(unmanned aerial vehicle: UAV)์˜ ๋น„ํ–‰ ์ œ์–ด๋ฅผ ์œ„ํ•œ ์ƒˆ๋กœ์šด ํ”„๋ ˆ์ž„์›Œํฌ๊ฐ€ ์ œ์•ˆ๋œ๋‹ค. ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ ๋ชจํ•‘ ๊ตฌ๋™๊ธฐ์˜ ๋™์  ํŠน์„ฑ์„ ๊ณ ๋ คํ•œ ํšก๋ฐฉํ–ฅ์ถ•(lateral-directional) ์šด๋™ ์ œ์–ด๋ฅผ ์œ„ํ•ด ๋น„๋Œ€์นญ ์ŠคํŒฌ ๋ชจํ•‘์„ ์‚ฌ์šฉํ•˜๊ณ  ์ข…์ถ•(longitudinal) ๋น„ํ–‰ ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ์œ„ํ•ด ๋Œ€์นญ ์ŠคํŒฌ ๋ชจํ•‘์˜ ์ด์ ์„ ํ™œ์šฉํ•œ๋‹ค. ๋˜ํ•œ ์„ค๊ณ„๋œ ์ œ์–ด ์‹œ์Šคํ…œ์€ ์„ ํ˜• ํŒŒ๋ผ๋ฏธํ„ฐ ๊ฐ€๋ณ€(linear parameter-varying: LPV) ๊ธฐ๋ฒ•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ œ์–ด๊ธฐ ์ด๋“์ด ์ž์ฒด์ ์œผ๋กœ ์Šค์ผ€์ค„๋ง ๋˜๋ฉฐ ๋ชจํ•‘ ํ˜•์ƒ ๋ฐ ๋น„ํ–‰ ์กฐ๊ฑด์˜ ์ž„์˜์˜ ๋ณ€ํ™”์— ๋Œ€ํ•ด ์•ˆ์ •์„ฑ๊ณผ ์„ฑ๋Šฅ์„ ์—„๋ฐ€ํ•˜๊ฒŒ ๋ณด์žฅํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๋ชจํ•‘ UAV๋Š” ๊ธฐ๋™ ๋ช…๋ น๊ณผ ๋น„ํ–‰ ์กฐ๊ฑด์— ๋”ฐ๋ผ ์•ˆ์ •์„ฑ์„ ์ƒ์‹คํ•  ์šฐ๋ ค ์—†์ด ์‹œ์Šคํ…œ ์ˆ˜์ค€์˜ ์ด์ ์„ ๊ทน๋Œ€ํ™”ํ•˜๋Š” ๋™์‹œ์— ๋‚ด๋ถ€ ๋ฃจํ”„ ์•ˆ์ •ํ™”๋ฅผ ์œ„ํ•œ ์ œ์–ด์— ๊ธฐ์—ฌํ•˜๋„๋ก ์ตœ์ ์˜ ํ˜•์ƒ์œผ๋กœ ์‹ ์†ํ•˜๊ฒŒ ๋ณ€ํ˜•๋  ์ˆ˜ ์žˆ๋‹ค. ์ฒซ์งธ, NASA GTM(generic transport model)์œผ๋กœ๋ถ€ํ„ฐ ๋น„๋Œ€์นญ ๊ฐ€๋ณ€ ์ŠคํŒฌ ๋ชจํ•‘ UAV์˜ ๊ณ ์ถฉ์‹ค๋„(high-fidelity) ๋น„์„ ํ˜• ๋ชจ๋ธ์ด ํš๋“๋œ๋‹ค. ๋ชจํ•‘์ด ์งˆ๋Ÿ‰ ์ค‘์‹ฌ, ๊ด€์„ฑ ํ–‰๋ ฌ ๋ฐ ๊ณต๊ธฐ์—ญํ•™ ๊ณ„์ˆ˜์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์€ ๋‚ ๊ฐœ๊ฐ€ ๋น„๋Œ€์นญ์ ์œผ๋กœ ์†์ƒ๋œ ๋ชจ๋ธ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๋„์ถœ๋œ๋‹ค. ์ขŒ์šฐ ๋‚ ๊ฐœ์˜ ์ŠคํŒฌ ๋ณ€ํ™”์œจ์€ ๋Œ€์นญ ๋ฐ ๋น„๋Œ€์นญ ๋ชจํ•‘ ํŒŒ๋ผ๋ฏธํ„ฐ๋กœ ๋ถ„ํ•ด๋˜๋ฉฐ, ๋‘ ๋ชจํ•‘ ํŒŒ๋ผ๋ฏธํ„ฐ๋Š” ๊ฐ๊ฐ ์Šค์ผ€์ค„๋ง ํŒŒ๋ผ๋ฏธํ„ฐ ๋ฐ ์ œ์–ด ์ž…๋ ฅ์œผ๋กœ ๊ฐ„์ฃผ๋œ๋‹ค. ๋น„์„ ํ˜• ๋ชจ๋ธ์„ ์ข…์ถ• ๋ฐ ํšก๋ฐฉํ–ฅ์ถ• ์šด๋™์œผ๋กœ ๋ถ„๋ฆฌํ•˜๊ณ  ์ง์‚ฌ๊ฐํ˜• ํ˜•ํƒœ์˜ ์Šค์ผ€์ค„๋ง ํŒŒ๋ผ๋ฏธํ„ฐ ์˜์—ญ์˜ ๊ฐ ๊ฒฉ์ž์ ์—์„œ ์„ ํ˜•ํ™”ํ•จ์œผ๋กœ์จ ๊ฐ ์ ์— ๋Œ€ํ•œ ์„ ํ˜• ์‹œ๋ถˆ๋ณ€(linear time-invariant: LTI) ๋ชจ๋ธ์ด ์–ป์–ด์ง„๋‹ค. LTI ๋ชจ๋ธ ์ง‘ํ•ฉ์— ๋ณด๊ฐ„(interpolation)์„ ์ ์šฉํ•˜๋ฉด ์ข…์ถ• ๋ฐ ํšก๋ฐฉํ–ฅ์ถ• ์šด๋™์— ๋Œ€ํ•œ ๋ชจํ•‘ UAV์˜ LPV ๋ชจ๋ธ์ด ์–ป์–ด์ง„๋‹ค. ๋‘˜์งธ, ์ˆ˜์ง ๊ฐ€์†๋„(normal acceleration) ๋ช…๋ น๊ณผ ์˜†๋ฏธ๋„๋Ÿผ๊ฐ(angle of sideslip) ๋ฐ ๋กค ๊ฐ์†๋„ ๋ช…๋ น ์ถ”์ข…์„ ์œ„ํ•ด LPV ๊ธฐ๋ฒ•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ข…์ถ• ๋ฐ ํšก๋ฐฉํ–ฅ์ถ• ์ œ์–ด ์ฆ๊ฐ• ์‹œ์Šคํ…œ(control augmentation system)์ด ์„ค๊ณ„๋œ๋‹ค. ์ด๋•Œ, ์ œ์–ด ์„ค๊ณ„ ๊ณผ์ •์—์„œ ์ฃผํŒŒ์ˆ˜์ข…์†(frequency-dependent) ๊ฐ€์ค‘์น˜ ํ•„ํ„ฐ๋ฅผ ํ†ตํ•ด ๋‚ฎ์€ ๋Œ€์—ญํญ(bandwidth)๊ณผ ๊ฐ™์€ ๋ชจํ•‘ ๊ตฌ๋™๊ธฐ ๊ณ ์œ ์˜ ๋™์  ํŠน์„ฑ์ด ๊ณ ๋ ค๋œ๋‹ค. ๋˜ํ•œ ๋น„ํ–‰ ํŠน์„ฑ์— ๋Œ€ํ•œ ๋ชจํ•‘์˜ ๋‹ค์–‘ํ•œ ์˜ํ–ฅ์„ ๊ณ ๋ คํ•˜์—ฌ ์‹คํ–‰ํ•˜๊ณ ์ž ํ•˜๋Š” ๊ธฐ๋™์„ ๋ณด์กฐํ•˜๊ธฐ ์œ„ํ•œ ์ŠคํŒฌ ๋ชจํ•‘ ์ „๋žต์ด ๋…ผ์˜๋œ๋‹ค. Pushover-pullup ๊ธฐ๋™ ๋ฐ high-g turn์— ๋Œ€ํ•œ ์ˆ˜์น˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์ด ํƒ€๋‹นํ•จ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋Œ€๊ธฐ์†๋„(airspeed) ๋ฐ ๊ณ ๋„ ๋ช…๋ น๊ณผ ์˜†๋ฏธ๋„๋Ÿผ๊ฐ ๋ฐ ๋กค ๊ฐ ๋ช…๋ น์„ ์ถ”์ข…ํ•˜๊ธฐ ์œ„ํ•ด LPV ๊ธฐ๋ฒ•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ข…์ถ• ๋ฐ ํšก๋ฐฉํ–ฅ์ถ• ์ž๋™ ์กฐ์ข… ์žฅ์น˜(autopilot)๊ฐ€ ์„ค๊ณ„๋œ๋‹ค. ์ด๋•Œ, 3์ฐจ์› ๊ฒฝ๋กœ ์ถ”์ข…์„ ์œ„ํ•ด ๋น„์„ ํ˜• ์œ ๋„ ๋ฒ•์น™์ด ์ž๋™ ์กฐ์ข… ์žฅ์น˜์™€ ๊ฒฐํ•ฉ๋œ๋‹ค. ๊ฒฝ๋กœ ์ถ”์ข… ๋น„ํ–‰์— ๋Œ€ํ•œ ์ˆ˜์น˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์Šค์ผ€์ค„๋ง ํŒŒ๋ผ๋ฏธํ„ฐ์˜ ๋ณ€ํ™” ์†๋„๊ฐ€ ๋น ๋ฅด๊ฑฐ๋‚˜ ๋ณ€ํ™”์˜ ํญ์ด ๋„“์€ ๊ฒฝ์šฐ ์ผ๋ฐ˜์ ์ธ ์ด๋“์Šค์ผ€์ค„ ์ œ์–ด๊ธฐ๋Š” ์•ˆ์ •์„ฑ์„ ์ƒ์‹คํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐ˜๋ฉด ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ ๋งŒ์กฑํ•  ๋งŒํ•œ ์„ฑ๋Šฅ์„ ์œ ์ง€ํ•จ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ๋‹ค.1 Introduction 1 1.1 Background and Motivation 1 1.2 Literature Review 6 1.2.1 Fixed-Wing Aircraft Implementing Morphing Technologies 6 1.2.2 Flight Control of Morphing Aircraft 7 1.2.3 Gain Scheduling Approaches to Controller Design 7 1.3 Objectives and Contributions 9 1.3.1 Objectives 9 1.3.2 Contributions 9 1.4 Dissertation Outline 11 2 Mathematical Preliminaries 13 2.1 LPV Systems 15 2.1.1 Taxonomy of Dynamical Systems 15 2.1.2 Definition of LPV Systems 15 2.1.3 LPV Modeling by Linearization 20 2.2 Gain Self-Scheduled Induced L2-Norm Control of LPV Systems 25 2.2.1 Norms of Signals and Systems 25 2.2.2 Analysis of LPV Systems 26 2.2.3 LPV Controller Design 30 2.2.4 Software for Synthesis and Analysis 30 3 Asymmetric Variable-Span Morphing UAV Model 33 3.1 Nonlinear Model of a Morphing UAV 36 3.1.1 Nominal Model of a Baseline Model 36 3.1.2 Morphing UAV Model 41 3.2 Derivation of an LPV Model of a Morphing UAV 52 3.2.1 Trim Analysis and Scheduling Parameter Selection 52 3.2.2 Pointwise Linearization of a Nonlinear Model 55 3.2.3 Linear Parameter-Varying Modeling and Analysis 58 4 CAS Design Based on LPV Method for Morphing-Assisted Maneuvers 61 4.1 Longitudinal CAS Design for Normal Acceleration Control 65 4.1.1 Performance Specifications 65 4.1.2 Controller Synthesis and Analysis 68 4.2 Lateral-Directional CAS Design for Turn Coordination and Roll Rate Control 73 4.2.1 Performance Specifications 73 4.2.2 Controller Synthesis and Analysis 75 4.3 Span Morphing Strategy 83 4.3.1 Effects of Span Morphing 83 4.3.2 Criteria for Span Variation 85 4.4 Nonlinear Simulation of Morphing-Assisted Maneuvers 86 4.4.1 High-Fidelity Flight Dynamics Simulator 86 4.4.2 Push-over and Pull-up 86 4.4.3 High-g Turn 89 5 Autopilot Design Based on LPV Methods for Morphing-Assisted Flights 109 5.1 Longitudinal Autopilot Design for Airspeed and Altitude Control 111 5.1.1 Performance Specifications 111 5.1.2 Controller Synthesis and Analysis 113 5.2 Lateral-Directional Autopilot Design for Turn Coordination and Roll Angle Control 121 5.2.1 Performance Specifications 121 5.2.2 Controller Synthesis and Analysis 123 5.3 Nonlinear Guidance Law for Trajectory Tracking 131 5.4 Nonlinear Simulation of Morphing-Assisted Flights 132 5.4.1 Waypoint Following at Low Altitude 132 5.4.2 Circular Trajectory Tracking at High Altitude 132 5.4.3 Helical Ascent under Fast Morphing 132 5.4.4 Spiral Descent with Morphing Scheduling 139 6 Conclusion 147 6.1 Concluding Remarks 147 6.2 Future Work 148๋ฐ•

    Gain-scheduled Hโˆž control via parameter-dependent Lyapunov functions

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    Synthesising a gain-scheduled output feedback Hโˆž controller via parameter-dependent Lyapunov functions for linear parameter-varying (LPV) plant models involves solving an infinite number of linear matrix inequalities (LMIs). In practice, for affine LPV models, a finite number of LMIs can be achieved using convexifying techniques. This paper proposes an alternative approach to achieve a finite number of LMIs. By simple manipulations on the bounded real lemma inequality, a symmetric matrix polytope inequality can be formed. Hence, the LMIs need only to be evaluated at all vertices of such a symmetric matrix polytope. In addition, a construction technique of the intermediate controller variables is also proposed as an affine matrix-valued function in the polytopic coordinates of the scheduled parameters. Computational results on a numerical example using the approach were compared with those from a multi-convexity approach in order to demonstrate the impacts of the approach on parameter-dependent Lyapunov-based stability and performance analysis. Furthermore, numerical simulation results show the effectiveness of these proposed techniques
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