Showing papers by "Petar V. Kokotovic published in 1994"
TL;DR: Model reference adaptive controllers are designed for plants with unknown dead-zones in which two sets of adjustable parameters, one belonging to a dead-zone inverse and the other to a linear controller, are kept fixed or adaptively updated.
Abstract: Model reference adaptive controllers are designed for plants with unknown dead-zones. Several control strategies are investigated in which two sets of adjustable parameters, one belonging to a dead-zone inverse and the other to a linear controller, are either kept fixed or adaptively updated. The developed adaptive control schemes ensure boundedness of all closed-loop signals and reduce the tracking error. >
442 citations
TL;DR: A new approach to adaptive control oflinear systems abandons the traditional certainty-equivalence concept and treats the control of linear plants with unknown parameters as a nonlinear problem, which significantly improves transient performance without an increase in control effort.
Abstract: A new approach to adaptive control of linear systems abandons the traditional certainty-equivalence concept and treats the control of linear plants with unknown parameters as a nonlinear problem. A recursive design procedure introduces at each step new design parameters and incorporates them in a novel Lyapunov function. This function encompasses all the states of the adaptive system and forces them to converge to a manifold of smallest possible dimension. Only as many controller parameters are updated as there are unknown plant parameters, and the dynamic order of the resulting controllers is no higher (and in most cases is lower) than that of traditional adaptive schemes. A simulation comparison with a standard indirect linear scheme shows that the new nonlinear scheme significantly improves transient performance without an increase in control effort. >
224 citations
01 Jan 1994
TL;DR: In this paper, a new class of controllers for dynamic feedback linearizable systems which achieve asymptotic tracking of given state reference trajectories is presented, characterized by a formula whose design parameters directly describe the trade-off between control effort and tracking error.
Abstract: Presents a new class of controllers for dynamic feedback linearizable systems which achieve asymptotic tracking of given state reference trajectories. These controllers are characterized by a formula whose design parameters directly describe the trade-off between control effort and tracking error. For natural choices of these design parameters, this formula generates controllers which do not blindly cancel nonlinearities but rather counteract them only when they degrade the performance of the system. Furthermore, these controllers are optimal with respect to sensible performance criteria and therefore possess desirable robustness properties.
97 citations
29 Jun 1994
TL;DR: Three new adaptive nonlinear output-feedback schemes are presented, one of which employs the tuning functions technique, while the other two employ a novel estimation-based approach.
Abstract: Three new adaptive nonlinear output-feedback schemes are presented. The first scheme employs the tuning functions technique, while the other two employ a novel estimation-based approach.
52 citations
TL;DR: A state feedback control is presented which achieves asymptotic tracking of signals generated by a known exosystem for single-input single-output nonlinear systems with unknown parameters entering linearly.
Abstract: A state feedback control is presented which achieves asymptotic tracking of signals generated by a known exosystem for single-input single-output nonlinear systems with unknown parameters entering linearly. The following assumptions are required: the nominal system is feedback linearizable; the tracking dynamics are not affected by unknown parameters; the linear approximation of the zero dynamics has no eigenvalue with zero real part; pure feedback conditions are satisfied on the vector fields multiplying unknown parameters. This extends to a class of nonlinear uncertain systems output regulator theory given in Isidori-Byrnes (1990) and provides adaptive tracking for systems which may have unbounded tracking dynamics. >
44 citations
TL;DR: A recently proposed recursive design of adaptive controllers for minimum phase linear systems with known but arbitrary relative degree is presented from a passivity perspective and stability is deduced from the well-known links between passivity and Lyapunov stability.
43 citations
14 Dec 1994
TL;DR: In this paper, the authors consider nonlinear systems with stable linear unmodeled dynamics at the input and propose a dynamic feedback design which guarantees global boundedness in the presence of input unmodelled dynamics.
Abstract: Considers nonlinear systems with stable linear unmodeled dynamics at the input. First the authors illustrate the main instability mechanisms on an example. Then the authors propose a dynamic feedback design which guarantees global boundedness in the presence of input unmodeled dynamics. The authors apply this design to feedback linearizable systems, for which global asymptotic stability is also achieved. >
30 citations
14 Dec 1994
TL;DR: Using the concept of a robust control Lyapunov function, robust backstepping tools are presented and it is demonstrated how they can be used in systematic design procedures.
Abstract: We review some of the existing results on the Lyapunov design of robustly stabilizing feedback laws for uncertain nonlinear systems. Using the concept of a robust control Lyapunov function, we present robust backstepping tools and demonstrate how they can be used in systematic design procedures. >
23 citations
14 Dec 1994
TL;DR: In this paper, the authors extend the concept of robust control Lyapunov function (RCLF) for nonlinear systems to the case of measurement feedback and explore conditions under which the existence of an RCLF is sufficient and/or necessary for robust global stabilizability via continuous static or dynamic measurement feedback.
Abstract: We extend the concept of a robust control Lyapunov function (RCLF) for nonlinear systems to the case of measurement feedback. We explore conditions under which the existence of an RCLF is sufficient and/or necessary for robust global stabilizability via continuous static or dynamic measurement feedback. >
10 citations
14 Dec 1994
TL;DR: In this article, a unified discrete-time adaptive inverse approach is developed for control of systems with unknown nonsmooth input nonlinearities such as dead-zone, backlash and hysteresis characteristics.
Abstract: A unified discrete-time adaptive inverse approach is developed for control of systems with unknown nonsmooth input nonlinearities such as dead-zone, backlash and hysteresis characteristics The proposed controller structure consists of an adaptive inverse for cancelling the effect of an unknown nonlinearity and a fixed (or adaptive) linear part for a known (or unknown) linear dynamics, which leads to a linearly parametrized error system suitable for adaptation, improves tracking performance and ensures closed-loop signal boundedness >
8 citations
29 Jun 1994
TL;DR: In this article, an adaptive hysteresis inverse controller for closed-loop error systems is proposed, based on which linear adaptive control theory is applied to develop adaptive laws to update the controller parameters.
Abstract: We develop an inverse for a parametrized hysteresis model and present its discrete-time version. We then design two adaptive hysteresis inverse controllers for discrete time systems with an unknown hysteresis at the output: one for systems with a known linear part-followed by an unknown hysteresis and the other for both the linear part and the hysteresis unknown. Our control schemes consist of a linear feedforward part and a linear-like feedback part combined with an adaptive hysteresis inverse. Despite the bilinear appearance of the parameters of the linear part and the hysteresis, a linear parametrization of the closed-loop error system is achieved, based on which we apply the linear adaptive control theory to develop adaptive laws to update the controller parameters.