Linear active disturbance rejection control of the hovercraft vessel model

A linearizing robust dynamic output feedback control scheme is proposed for earth coordinate position variables trajectory tracking tasks in a hovercraft vessel model. The controller design is carried out using only position and orientation measurements. A highly simplified model obtained from flatness considerations is proposed which vastly simplifies the controller design task. Only the order of integration of the input-to-flat output subsystems, along with the associated input matrix gain, is retained in the simplified model. All the unknown additive nonlinearities and exogenous perturbations are lumped into an absolutely bounded, unstructured, vector of time signals whose components may be locally on-line estimated by means of a high gain Generalized Proportional Integral (GPI) observer. GPI observers are the dual counterpart of GPI controllers providing accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and endogenous perturbation inputs. These observers exhibit remarkably convenient self-updating internal models of the unknown disturbance input vector components. These two key pieces of on-line information are used in the proposed feedback controller to conform an active disturbance rejection, or disturbance accommodation, control scheme. Simulation results validate the effectiveness of the proposed design method

Control of a DC motor using algebraic derivative estimation with real time experiments

This paper presents an experimental control scheme for DC motors which combines an overlapping implementation of the algebraic derivative estimation method and a disturbance estimator based on the aforementioned algebraic derivative method. The methodology only requires the measurement of the angular position of the motor and the voltage input to the motor. The main advantages of the proposed approach are: it is independent of the motor’s initial conditions, the methodology is robust to Coulomb friction effects, it does not require any statistical knowledge of the noises that corrupt the data, the derivative estimation process does not require initial conditions or dependence between the system input and output, and the algorithm is computed on-line and in real time. The effectiveness of the proposed controller has been verified by means of computer simulations and it has also been experimentally implemented on a laboratory prototype with excellent results in both, stabilization and trajectory tracking tasks

Phase synchronization of autonomous AC grid system with passivity-based control

This paper discusses a ring‐coupled buck‐type inverter system to harness energy from direct current (DC) sources of electricity. The DC‐DC buck converter circuit is modified with an H‐bridge to convert the DC input voltage to a usable alternating current (AC) output voltage. Passivity‐based control (PBC) with port‐controlled Hamiltonian modelling (PCHM) is a method where the system is controlled by considering not only the energy properties of the system but also the inherent physical structure. PBC is applied to achieve stabilization of the AC output voltage to a desired amplitude and frequency. Unsynchronized output voltages in terms of phase angle or frequency can cause detrimental effects on the system. Phase‐locked loop (PLL) is employed in the ring structure to maintain synchronization of the AC output voltage of all inverter units in the ring‐coupled system

Elimination Theory for Nonlinear Parameter Estimation

The work presented here exploits elimination theory (solving systems of polynomial equations in several variables) [1][2] to perform nonlinear parameter identification. In particular show how this technique can be used to estimate the rotor time constant and the stator resistance values of an induction machine. Although the example here is restricted to an induction machine, parameter estimation is applicable to many practical engineering problems. In [3], L. Ljung has outlined many of the challenges of nonlinear system identification as well as its particular importance for biological systems. In these types of problems, the model developed for analysis is typically a nonlinear state space model with unknown parameter values. The typical situation is that only a few of the state variables are measurable requiring that the system be reformulated as a nonlinear input-output model. In turn, resulting the nonlinear input-output model is almost always nonlinear in the parameters. Towards that end, differential algebra tools for analysis of nonlinear systems have been developed by Michel Fliess [4][5] and Diop [6]. Moreover, Ollivier [7] as well as Ljung and Glad [8] have developed the use of the characteristic set of an ideal as a tool for identification problems. The use of these differential algebraic methods for system identification have also been considered in [9], [10]. The focus of their research has been the determination of a priori identifiability of a given system model. However, as stated in [10], the development of an efficient algorithm using these differential algebraic techniques is still unknown. Here, in contrast, a method for which one can actually numerically obtain the numerical value of the parameters is presented. We also point out that [11] has also done work applying elimination theory to systems problems

Robust Linear Longitudinal Feedback Control of a Flapping Wing Micro Air Vehicle

This paper falls under the idea of introducing biomimetic miniature air vehicles in ambient assisted living and home health applications. The concepts of active disturbance rejection control and flatness based control are used in this paper for the trajectory tracking tasks in the flapping-wing miniature air vehicle (FWMAV) time-averaged model. The generalized proportional integral (GPI) observers are used to obtain accurate estimations of the flat output associated phase variables and of the time-varying disturbance signals. This information is used in the proposed feedback controller in (a) approximate, yet close, cancelations, as lumped unstructured time-varying terms, of the influence of the highly coupled nonlinearities and (b) the devising of proper linear output feedback control laws based on the approximate estimates of the string of phase variables associated with the flat outputs simultaneously provided by the disturbance observers. Numerical simulations are provided to illustrate the effectiveness of the proposed approach

A redundant dynamical sliding mode control scheme for an asymptotic space vehicle stabilization

International audienc