version: "1.0.0" name: gnc-autonomy description: "Use when a task concerns guidance, navigation, and control for aerospace vehicles: guide the router to the gnc-autonomy pack: orbit-dynamics Hohmann and J2 drift, rendezvous-phasing phasing maneuvers, attitude-dynamics quaternion kinematics, navigation-frames ECEF/NED/WGS-84, inertial-navigation INS drift and Schuler, dilution-of-precision GDOP/PDOP, python-control-design PID margins, root-locus-design closed-loop poles, state-space-analysis controllability, pid-control-design Ziegler-Nichols, lqr-design Riccati gains, dymos-trajectory pseudospectral optimization, proportional-navigation the PN law, command-to-line-of-sight CLOS guidance, pursuit-guidance capture conditions, kalman-filter-design state estimation. Trigger: GNC, navigation, control, orbit dynamics, Hohmann, rendezvous, attitude dynamics, quaternion, ECEF/NED/WGS-84, INS, Schuler, dilution of precision, GDOP, PID, root locus, controllability, proportional navigation, command to line of sight, pursuit guidance, kalman filter, state estimation." license: Apache-2.0 compliance: STANDARDS-REF standards:

• id: arp4754a

reference-only: true

• id: ecss

reference-only: true gated: false domain: gnc-autonomy pack: gnc-autonomy compatibility: "agentskills.io SKILL.md; router/entry point for the gnc-autonomy domain pack" metadata: domain: gnc-autonomy tags: [] version: 0.1.0 author: Aero Agent Skills

GNC and autonomy domain pack (router)

Route here when the task is guidance, navigation, and control: orbital mechanics, control system design, trajectory optimization, or guidance laws.

Domain

GNC and autonomy: space orbit dynamics (propagation, maneuvers, J2), rendezvous phasing, navigation frames (ECEF/NED/geodetic), inertial navigation, classical control design (margins, tuning), state-space control (root locus, LQR), pseudospectral trajectory optimization, and guidance laws (proportional navigation, pursuit).

Sub-skills in this pack

Routing guidance

• Orbit and maneuver questions route to the orbit-dynamics sub-skill.
• Phasing and rendezvous planning questions route to the

rendezvous-phasing sub-skill.

• Attitude dynamics, quaternion kinematics, and momentum questions

route to the space attitude-dyn- Mpc questions route to the optimal-control model-predictive-control sub-skill. amics sub-skill.

• Coordinate-frame and navigation-solution questions (ECEF/NED/geodetic,

WGS-84) route to the navigation navigation-frames sub-skill.

• Inertial navigation, drift, and Schuler questions route to the

navigation inertial-navigation sub-skill.

• DOP, satellite geometry, and subset-selection questions route to the

navigation dilution-of-precision sub-skill.

• Controller design and margin questions route to the

python-control-design sub-skill.

• Root-locus questions (pole trajectories, gain for target damping)

route to the control root-locus-design sub-skill.

• State-space controllability, observability, transition-matrix, and

canonical-form questions route to the control state-space-analysis sub-skill.

• PID gain tuning, Ziegler-Nichols, and anti-windup questions route to

the control pid-control-design sub-skill.

• LQR and Riccati-gain questions route to the optimal-control

lqr-design sub-skill.

• Optimal control and trajectory questions route to the

dymos-trajectory sub-skill.

• Proportional navigation and intercept guidance questions route to

the guidance proportional-navigation sub-skill.

• Pure pursuit, lead pursuit, and capture-condition questions route

to the guidance pursuit-guidance sub-skill.

• Ballistic impact point, range equation, time of flight, and launch

speed and angle sensitivity questions route to the guidance impact-point-prediction sub-skill.

• Midcourse waypoint steering, trajectory shaping, velocity-to-be-gained,

zero-effort-miss, and terminal handover questions route to the guidance midcourse-guidance sub-skill.

• Certification and item-level assurance questions route to the

avionics or systems-engineering-safety packs.

• Kalman filtering, state estimation, and sensor fusion questions route to the navigation kalman-filter-design sub-skill.
• Command-to-line-of-sight and LOS error steering questions route to the guidance command-to-line-of-sight sub-skill.
• Phase lead/lag compensator, phase margin boost, crossover placement, and steady state error constant questions route to the control lead-lag-compensation sub-skill.
• Bode frequency response, gain crossover, phase crossover, gain margin, and phase margin questions route to the control frequency-response-design sub-skill.
• Gain schedule breakpoint tables, scheduling variables (dynamic pressure, Mach), and gain interpolation questions route to the control gain-scheduling sub-skill.
• Full-order state observer design, observability checks, estimator gain pole placement, and separation principle questions route to the control observer-design sub-skill.
• Alpha-beta tracking, constant velocity target, smoothing factor, steady state gain, and position and velocity tracking questions route to the estimation-filtering alpha-beta-filter sub-skill.
• Sigma-point nonlinear state estimation, scaled unscented transform, UKF predict and update, and innovation covariance checks route to the estimation-filtering unscented-kalman-filter sub-skill.
• Estimation-bound questions (Fisher information, Cramer-Rao lower bound for scalar and vector estimators, DC level in Gaussian noise, estimator efficiency against the bound) route to the estimation-filtering cramer-rao-lower-bound sub-skill.
• Extended Kalman filter design for nonlinear systems with Jacobian linearization, predict and update recursion, innovation covariance, and Kalman gain computation routes to the estimation-filtering extended-kalman-filter sub-skill.
• Control allocation across redundant effectors, pseudoinverse and weighted least squares, daisy chain, and actuator saturation redistribution questions route to the control control-allocation sub-skill.
• RAIM integrity questions (fault detection and exclusion, horizontal protection level, chi-square threshold, normalized residual) route to the navigation gnss-raim-fde sub-skill.
• Rauch-Tung-Striebel fixed-interval smoothing and backward-pass post-processing questions route to the estimation-filtering rts-smoother sub-skill.
• Coverage path planning, boustrophedon, and lawnmower aerial survey pattern questions route to the guidance coverage-path-planning sub-skill.
• Model-reference adaptive control questions (MRAC, adaptation law, tracking error convergence, unknown plant coefficient) route to the control adaptive-control sub-skill.
• L1 adaptive control questions (state predictor, projection-based adaptation law, low-pass-filtered adaptive signal, guaranteed transient response of the first-order uncertain plant) route to the control l1-adaptive-control sub-skill; first-order MRAC stays with adaptive-control.

• Interacting multiple model filter questions (IMM filter bank, mode probability, Markov mode switching, maneuvering target tracking, CV CA modes) route to the estimation-filtering interacting-multiple-model-filter sub-skill.
• Sampled-data digital control questions (z transform, Tustin bilinear emulation, frequency prewarping, zero order hold, discrete PID, unit circle stability) route to the control digital-control-design sub-skill.

• Time-optimal bang-bang control questions (switching curve, minimum-time rest-to-rest slew, double integrator) route to the optimal-control bang-bang-control sub-skill.
• code-carrier Hatch smoothing time constant, carrier delta range, code-carrier ionospheric divergence, smoothed range noise reduction questions route to the navigation gnss-carrier-smoothing sub-skill.
• linear-quadratic-Gaussian output-feedback compensator, regulator and filter Riccati gains, separation principle questions route to the optimal-control lqg-design sub-skill.
• Loop-transfer-recovery questions (LQG output loop recovery by filter noise weight inflation, full-state-loop matching, recovery-gain tuning, target feedback loop) route to the optimal-control loop-transfer-recovery sub-skill.
• Ionospheric delay correction questions (Klobuchar broadcast model slant delay, alpha and beta coefficient polynomials, pierce-point geometry, L1 pseudorange delay removal) route to the navigation ionospheric-delay-correction sub-skill; carrier-smoothed code divergence stays with gnss-carrier-smoothing.
• Impact-time-control questions (salvo and simultaneous-impact guidance, commanded impact time, time-to-go error feedback, simultaneous-impact-guidance law) route to the guidance impact-time-control-guidance sub-skill.
• Tropospheric delay correction questions (Saastamoinen zenith dry and wet delay, elevation-angle mapping to slant delay, pressure temperature humidity inputs) route to the navigation tropospheric-delay-correction sub-skill; ionospheric Klobuchar delay stays with ionospheric-delay-correction.
• Impact-angle-constrained guidance questions (terminal flight-path-angle control, biased proportional navigation, trajectory-shaping guidance laws) route to the guidance impact-angle-control-guidance sub-skill; impact-time control stays with impact-time-control-guidance.
• Smith predictor questions (dead-time compensation, predictor structure for time-delayed plants, delay-free characteristic equation) route to the control smith-predictor sub-skill; PID tuning and digital emulation stay with pid-control-design and digital-control-design.
• H-infinity control questions (mixed-sensitivity S/KS loop shaping, H-infinity norm computation, robustness weights) route to the control h-infinity-control sub-skill; LQR and LQG synthesis stay with lqr-design and lqg-design.
• passive angle-of-arrival bearing lines, Stansfield weighted least squares emitter fix, bearing-line error ellipse questions route to the navigation bearing-only-localization sub-skill.
• H-infinity synthesis questions (DGKF two-Riccati state-space synthesis, gamma iteration, spectral-radius coupling condition, central controller) route to the control h-infinity-synthesis sub-skill; mixed-sensitivity S/KS norm analysis of a given pair stays with h-infinity-control.
• Sliding-mode control questions (sliding surface design, equivalent control, reaching law, chattering suppression) route to the control sliding-mode-control sub-skill; model-reference and L1 adaptation stay with adaptive-control and l1-adaptive-control.
• Feedback-linearization questions (input-output linearization, relative degree, zero-dynamics stability, nonlinearity-cancelling control law) route to the control feedback-linearization sub-skill; variable-structure control stays with sliding-mode-control.

Install

To install only this pack, copy or symlink each leaf folder above into your host's skills directory (see README Install for per-host commands).

• Particle filter and non-Gaussian nonlinear estimation questions route to the estimation-filtering particle-filter sub-skill.
• Mahony complementary-filter attitude estimation and gyro-bias questions route to the estimation-filtering complementary-filter sub-skill.
• Dubins minimum-turn path generation between heading-constrained poses and CSC/CCC path family questions route to the guidance dubins-path-planning sub-skill.
• Single-epoch GNSS pseudorange position and clock-bias fixes route to the navigation gnss-pseudorange-positioning sub-skill.
• Collision-course intercept questions (lead angle, constant bearing, collision triangle, predicted intercept point) route to the guidance collision-course-guidance sub-skill.
• Augmented proportional navigation questions (target lateral acceleration term, maneuvering target intercept, APN command) route to the guidance augmented-proportional-navigation sub-skill.
• Gibbs and Herrick-Gibbs initial orbit determination from three position vectors routes to the space orbit-determination sub-skill.

• Loosely coupled INS/GNSS integration questions (error-state filter propagation with the psi-angle model, GNSS position updates, INS drift correction) route to the navigation ins-gnss-integrated-filter sub-skill.
• Tightly coupled INS/GNSS questions (raw-pseudorange measurement updates, clock bias and drift states, INS error-state filter on the raw observables) route to the navigation tightly-coupled-ins-gnss sub-skill.
• GNSS receiver-velocity questions (carrier delta-range-rate doppler observables, iterated least-squares velocity and clock-drift fix) route to the navigation gnss-doppler-velocity-positioning sub-skill.
• Process-noise discretization questions (van Loan method, continuous spectral density to discrete covariance, filter Q design) route to the estimation-filtering process-noise-discretization sub-skill.
• Nonlinear finite-horizon trajectory optimization questions (iterative LQR, differential dynamic programming, backward Riccati pass) route to optimal-control ilqr-ddp; terrain/map-aided INS questions (TERCOM correlation, DEM matching, SITAN terrain-slope update) route to navigation terrain-referenced-navigation; carrier-phase differential positioning (double differences, integer ambiguity resolution) routes to navigation gnss-rtk-positioning.
• IMU static calibration questions (six-position accelerometer test, rate-table gyro calibration, bias and scale factor estimation) route to the estimation-filtering imu-static-calibration sub-skill.
• Backstepping questions (strict-feedback recursive design, error-variable recursion, virtual control, analytic virtual-control derivative, control-Lyapunov decay audit) route to the control backstepping-control sub-skill; model-reference and L1 adaptation stay with adaptive-control and l1-adaptive-control; switching laws stay with sliding-mode-control.
• Active-disturbance-rejection questions (linear-extended-state-observer bandwidth parameterization, total-disturbance estimation, disturbance-rejection term) route to the control active-disturbance-rejection-control sub-skill; classical PID tuning stays with pid-control-design; model-reference and L1 adaptation stay with adaptive-control and l1-adaptive-control.
• Adaptive-backstepping questions (tuning-function design, parameter estimate updated by the second tuning function carried through the z1 z2 error recursion, theta-hat virtual control, augmented Lyapunov function with the parameter-error term, parameter-error convergence) route to the control adaptive-backstepping sub-skill; exact-model strict-feedback recursion stays with backstepping-control; model-reference and L1 adaptation stay with adaptive-control and l1-adaptive-control.