Exploration and mapping of an unknown flight envelope

Retrospective Cost Adaptive PID Control of Quadcopter/Fixed-Wing Mode Transition in a VTOL Aircraft

“…In, 10,11,[16][17][18] G f is based on the Markov parameters of the control-to-performance transfer matrix G zu . In particular, for all complex numbers z whose absolute value is greater than the spectral radius of A, it follows that…”

Retrospective Cost Adaptive Control of the Generic Transport Model under Abrupt Faults

“…In, 17,[25][26][27][28] the filter G f is based on the Markov parameters of the control-to-performance transfer matrix G zu . In particular, for all complex numbers z whose absolute value is greater than the spectral radius of A, it follows that…”

Retrospective Cost Adaptive Control of Generic Transport Model Under Uncertainty and Failure

“…where z z 1 z 2 z 3 z 4 T and z 1 , z 2 , z 3 , z 4 are the components of z in Eq. (28), which is the vector of command-following errors. The vector θ i of controller coefficients has the same size as ϕ i .…”

“…T s 0.1 s is the sampling time, zk is given by Eq. (28), and the gain matrices K 1 and K 2 are obtained using the linearization A; B; C with state weighting R 1 I 13×13 and control weighting R 2 diag0.1; 0.1; 100; 100. Note that, with zk given by Eq.…”

“…We then consider a series of cases that examine the performance of RCAC under various conditions, including trim finding, startup, unknown time-varying aircraft dynamics (such as icing and mass variation), unknown flight envelope (including the possibility of conflicting commands), known sensing constraints (such as a failed air data system), known actuation constraints (requiring differential thrust), unknown sensor failure (stuck and biased airspeed measurement), and unknown actuator failure (such as anomalous stroke and rate saturation, dead zone, and jam). Some of these cases are considered in [24][25][26][27][28]. For each case, we consider a range of scenarios that capture various commands and performance objectives.…”