We consider systems that can be described by a linear part with a nonlinear perturbation, where the perturbation is parameterized by a vector of unknown, constant parameters. Under a set of technical assumptions about the perturbation and its relationship to the outputs, we present a modular design technique for estimating the system states and the unknown parameters. The design consists of a h...

We introduce a method of observer design for systems described by a linear part with a nonlinear perturbation, where the perturbation is parameterized by a vector of unknown, constant parameters. The design is modular, and consists of a modified high-gain observer that estimates the states of the system together with the full perturbation, and a parameter estimator. The parameter estimator is c...

Kiyohito NAGANO\dagger (11Lnnnnn!!!llll)))BggX) Abstract A linearly parameterized polymatroid intersection problem appears in the context of principal partitions. We consider a submodular intersection problem on a pair of strong-map sequences of submodular functions, which is an extension of the linearly parameterized polymatroid intersection problem to a nonlinearly parameterized one. We intro...

In many industrial practices, it needs a permanent magnet synchronous motor to provide enough torque, such as autonomous vehicle driving. the operation of motor, nonlinearly parameterized-uncertainties degrade control performances, causing instability speed and output torques. Based on analysis temperature effects friction torque model, composite controller is proposed in this paper which consi...

A critical enabling technology for electrified vehicles and renewable energy resources is battery energy storage. Advanced battery systems represent a promising technology for these applications, however their dynamics are governed by relatively complex electrochemical phenomena whose parameters degrade over time and vary across manufacturer. Moreover, limited sensing and actuation exists to mo...

Under an appropriate ISS condition, it is shown that global adaptive stabilization of a class of cascade systems with nonlinear parameterization is achievable by non-Lipschitz continuous partial-state adaptive regulator. This result complements the earlier work [10] on adaptive control of uncertain nonlinear systems with uncontrollable unstable linearization, which are impossible to be dealt wi...

In this note a new high performance least squares parameter estimator is proposed. The main features of the are: (i) global exponential convergence guaranteed for all identifiable linear regression equations; (ii) it incorporates forgetting factor allowing to preserve alertness time-varying parameters; (iii) thanks addition mixing step relies on set scalar equations ensuring superior transient ...

In this paper, a methodology for Lyapunov-based adaptive PID control for different nonlinearlyparameterized series and parallel PID realizations presented using simple first and second order dominant plants. The corresponding designs are based on using only the tracking error, its derivative, its integral, and the current value of the adaptive gains in order to update the PID gains. The convent...

A critical enabling technology for electrified vehicles and renewable energy resources is battery energy storage. Advanced battery systems represent a promising technology for these applications, however their dynamics are governed by relatively complex electrochemical phenomena whose parameters degrade over time and vary across material design. Moreover, limited sensing and actuation exists to...

In this paper, an innovative robust adaptive tracking control method for robotic systems with unknown dynamics using a nonlinearly parameterized Additive Recurrent Neural Network (ARNN) is proposed. The ARNN uses the Gaussian Radial Basis Functions (GRBF) as activation functions. Through this method the training laws of all GRBF parameters are determined. Additionally, the system is augmented w...