Input Design For Identification Research Articles

Identification of hydrodynamic coefficients of a ship manoeuvring model based on PRBS input

A new method is proposed to obtain accurate hydrodynamic coefficients of 3-DOF ship models. This method includes two parts: identification algorithm and identification input design. Firstly, the manoeuvring modeling group model of an underactuated ship is introduced. Secondly, the nonlinear model of the ship is converted into a linear form by using the X-swapping technique. An on-line identification law, which is introduced for identification under relaxed excitation conditions, is used to estimate the unknown hydrodynamic coefficients of the ship dynamic model. Thirdly, two Pseudo-Random Binary Sequence signals are chosen as the identification inputs to excite the rudder and the propeller, which can improve identification performance. Finally, a simulation example is put forward to demonstrate the effectiveness of the proposed identification method.

A practical approach to input design for modal analysis using subspace methods

A basic class of multivariate system identification input design methods is proposed. Only reliable numerical linear algebra is used. The underlying idea is to inject energy into the invariant eigenspace for a subset of preestimated plant eigenvalues. Standard Schur pseudotriangular factorisation is used to pretarget a subsequent singular value decomposition. Explicit state-space formulas are given. Examples indicate that the approach may be useful in some practical applications. The approach may be considered user-friendly.

Constrained signal design using approximate prior models with application to the tennessee eastman process

Identification input design is the first and very important step towards a successful data-driven modeling task. In this paper, a previously communicated input design method, based on an approximate a-priori steady state model, is extended to the case that the known approximate model at hand is a dynamic one. Several additional issues are also discussed including the iterative signal design and identification process and the derivation of the model uncertainty. As an important case study, the methodology is applied to the challenging Tennessee Eastman problem, which is widely used in process control study. The identification results of the proposed and prior methods are compared.

Multiple control input design for identification of light aircraft

This paper establishes a design technique for control input histories resulting in higher confidence levels in the estimate of lateral stability and control derivatives of light aircraft, and which cause dynamic motion favorable to reductions in numerical divergence tendencies in the identification algorithms. A combined aileron and rudder input design is demonstrated for the Cessna 172 aircraft.