초록 ▼

An adaptive control system (ACS) uses direct output feedback to control a plant. The ACS uses direct adaptive output feedback control developed for highly uncertain nonlinear systems, that does not rely on state estimation. The approach is also applicable to systems of unknown, but bounded dimension

An adaptive control system (ACS) uses direct output feedback to control a plant. The ACS uses direct adaptive output feedback control developed for highly uncertain nonlinear systems, that does not rely on state estimation. The approach is also applicable to systems of unknown, but bounded dimension, whose output has known, but otherwise arbitrary relative degree. This includes systems with both parameter uncertainty and unmodeled dynamics. The result is achieved by extending the universal function approximation property of linearly parameterized neural networks to model unknown system dynamics from input/output data. The network weight adaptation rule is derived from Lyapunov stability analysis, and guarantees that the adapted weight errors and the tracking error are bounded.

대표청구항 ▼

1. An adaptive control system (ACS) for controlling a plant based on at least one commanded output signal yc and an rth time-derivative of the commanded output signal yc(r), and a plant output signal y that is a function of the states existing in the plant, r being the relative degree of the plant o

1. An adaptive control system (ACS) for controlling a plant based on at least one commanded output signal yc and an rth time-derivative of the commanded output signal yc(r), and a plant output signal y that is a function of the states existing in the plant, r being the relative degree of the plant output signal y, the ACS comprising:a model inversion unit (MIU) coupled to receive a pseudo-control signal v and a plant output signal y, the MIU generating a control signal δc by inverting an approximate model of the plant dynamics, the MIU supplying the control signal δc to the plant for control thereof; a summing unit coupled to receive the rth time-derivative of the commanded output signal yc(r), a pseudo-control component signal vdc, and an adaptive control signal vad, the summing unit adding the rth time-derivative of the commanded output signal yc(r) and the pseudo-control component signal vdc, and subtracting the adaptive control signal vad, to generate the pseudo-control signal v; an error signal generator (ESG) coupled to receive the commanded output signal yc and optional derivatives thereof and the plant output signal y, the ESG generating a tracking error signal {tilde over (y)} by differencing corresponding signal components of the commanded output signal yc and optional derivatives thereof, and a plant output signal y; a linear controller having a linear dynamic compensator (LDC) coupled to receive the tracking error signal {tilde over (y)}, the LDC generating the pseudo-control component signal vdc based on the tracking error signal {tilde over (y)}, the pseudo-control component signal vdc for stabilizing the feedback linearized dynamics of the model inverted in the MIU, the LDC generating a transformed signal {tilde over (y)}ad based on the tracking error signal {tilde over (y)} so that a transfer function from an adaptive control signal vad to the transformed signal {tilde over (y)}ad is strictly positive real (SPR); an adaptive element having an error conditioning element coupled to receive the transformed signal {tilde over (y)}ad and at least one neural network basis function φ, the error conditioning element stable low-pass filtering the basis function φ to produce a filtered basis function φf and multiplying the filtered basis function φr by the transformed signal {tilde over (y)}ad to produce a training signal δ; and a neural network adaptive element (NNAE) coupled to receive the plant output signal y, the pseudo-control signal v, and the training signal δ, the NNAE having a neural network generating the adaptive control signal vad based on the plant output signal y and the pseudo-control signal v supplied as inputs to the neural network, the neural network generating the adaptive control signal vad by mapping the plant output signal y and a pseudo-control signal v to the adaptive control signal vad based on at least one basis function φ and at least one connection weight W, the neural network couple to output the basis function φ to the error conditioning element, the adaptive element using the training signal δ to update the basis function φ and at least one connection weight W of the neural network so that the adaptive control signal vad generated by the neural network is bounded. 2. An ACS as claimed in claim 1 wherein the LDC maps the tracking error signal {tilde over (y)} to the pseudo-control component signal vdc based on a transfer function Ndc(s)/Ddc(s), and the LDC maps the tracking error signal {tilde over (y)} to the transformed signal {tilde over (y)}ad based on a transfer function Nad(s)/Ddc(s), the transfer functions Ndc(s)/Ddc(s) and Nad(s)/Ddc(s) selected to assure boundedness of the tracking error signal {tilde over (y)}.3. An ACS as claimed in claim 1 further comprising:a delay element coupled to receive the plant output signal y and generating at least one delayed plant output signal yd as an additional input signal to the neural network to generate the adaptive control signal vad. 4. An ACS as claimed in claim 1 further comprising:a delay element coupled to receive the pseudo-control signal v and generating at least one delayed pseudo-control signal vd, the delay element coupled to supply the delayed pseudo-control signal vd as an additional input signal to the neural network to generate the adaptive control signal vad. 5. An ACS as claimed in claim 1 wherein the plant comprises at least one sensor sensing at least one state of the plant, and generating the plant output signal y based on the sensed plant state.6. An ACS as claimed in claim 1 wherein the plant comprises at least one actuator controlling the plant based on the command control signal δc.7. An ACS as claimed in claim 1 wherein the ACS is operated by a human operator, the ACS further comprising:an operator interface unit coupled to receive the plant output signal y, the operator interface unit generating a display signal based on the plant output signal y; the operator receiving the display signal from the operator interface unit, and producing control action to control the plant based on the display signal; and a command filter unit operable by the operator, the command filter unit generating the commanded output signal yc, and optional derivatives thereof, and the rth derivative yc(r) of the plant output signal y based on control action of the operator. 8. An ACS as claimed in claim 1 further comprising:an operator interface unit coupled to receive the plant output signal y, the operator interface unit generating a signal based on the plant output signal y; an operator coupled to receive the signal generated by the operator interface unit, and generating an operator signal to control the plant based on the signal generated by the operator interface unit; and a command filter unit operable by the operator, the command filter unit generating the commanded output signal yc and optional derivatives thereof, and the rth derivative yc(r) of the plant output signal y based on the operator signal. 9. An adaptive element (AE) of an adaptive control system (ACS) for controlling a plant based on a plant output signal y that is a function of the full plant state existing in a plant, a pseudo-control signal v used to control the plant, and a transformed signal {tilde over (y)}ad from a linear controller of the ACS, the adaptive element comprising:a neural network adaptive element (NNAE) comprising a neural network having at least one connection weight W and at least one basis function φ, the neural network coupled to receive the pseudo-control signal v and the plant output signal y; a delay element coupled to receive the plant output signal y and the pseudo-control signal v, and generating signals yd, vd that are delayed versions of the plant output signal y and the pseudo-control signal v; and an error conditioning element coupled to receive the transformed signal {tilde over (y)}ad and the basis function φ, and generating an error signal δ based thereon, the NNAE coupled to receive the error signal δ and adapting the connection weight W and the basis function φ to adaptively control unmodeled plant dynamics. 10. An adaptive element as claimed in claim 9 wherein the error conditioning element includes a filter and a multiplier, the filter operating on the basis function φ from the NNAE to produce a filtered basis function φf, the multiplier generating the error signal δ by multiplying the filtered basis function φf by the transformed signal {tilde over (y)}ad.11. An adaptive element as claimed in claim 10 wherein the filter operates on the basis function φ to produce the filtered basis function φf using a transfer function T1(s) that ensures boundedness of the connection weight W and a tracking error signal {tilde over (y)} generated by differencing a commanded output signal yc and the plant output signal y, the tracking error signal {tilde over (y)} provided to the linear controller of the ACS to generate the transformed signal {tilde over (y)}ad and the pseudo-control signal v.