This paper proposes a scheme for feedforward (FF) learning control for an unknown multi-input multi-output (MIMO) linear plant in the two-degree-of-freedom structure. Provided that a feedback (FB) control stabilizes the plant but gives a poor response property to reference signals, FF control with on-line learning of inverse dynamics improves the response significantly. In contrast to existing FF learning control schemes called feedback error learning, we propose a scheme that overcomes difficulties in MIMO plant with finite zeros. Numerical simulation is carried out to show the effectiveness of the proposed scheme.
This paper proposes a new scheme of on-line identification for feedforward (FF) learning control of an un known nonlinear multi-input multi-output (MIMO) plant free of zero dynamics. This is achieved by constructing a FF controller consisting of a bank of linear approximation models for various operating points, which are discretized and called scheduler. Conventional schemes used piecewise constant/linear interpolation techniques to address the discretiza tion. However, the accuracy of response shaping was insufficient. To improve the performance, we propose to take a basis function approach to tune the parameter of the FF controller. To verify the effectiveness of the proposed scheme, numerical simulation is carried out using the motion equation of a two-link manipulator.
The two-degree-of-freedom structure allows us to design independently feedforward and feedback controls for response shaping and stabilization, respectively. Feedforward control with on-line tuning is particularly promising for improvement of response, so that various schemes have been proposed in literature. This paper proposes yet another scheme along this direction with focus on the control structure as well as online tuning. The proposed scheme avoids transient instability by tuning both prefilter and feedforward controllers, which are linear in parameter. Numerical simulation is carried out to verify the effectiveness of the scheme.
The discrete-time predictor feedback system was designed to compensate for constant input delays based on dstep ahead state predictions in discrete-time linear time-invariant systems. The entire spectrum, initially investigated by numerical computation, shows that aside from the eigenvalues of A + BK, there are other eigenvalues located about the origin. Existing literature only focuses on the spectrum coinciding with that of A + BK, but, in this study, we extended previous results by considering the full state of the system to obtain the eigenvalues mathematically. In contrast to the continuous-time case, it is important to note that the discrete-time delay system is finitedimensional. From this viewpoint, we started our analysis from the state space representation to construct a proof that derives the poles of the closed-loop system. Furthermore, as a preliminary step, we attempt a frequency domain analysis by considering nonzero initial conditions in taking the Z-transform of the system with an example.
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