A global output-feedback controller for stabilization and tracking of underactuated ODIN: A spherical underwater vehicle

This paper presents a method to design an output-feedback controller that simultaneously solves global asymptotic stabilization and tracking of an underactuated omni-directional intelligent navigator—a spherical underwater vehicle moving in a horizontal plane (i.e. at a constant depth). The vehicle does not have a sway actuator and has only position and orientation measurements available. The control development is based on Lyapunov's direct method, backstepping technique and use of interconnected structure of the vehicle dynamics. Numerical simulations demonstrate the results.     

Adaptive switching supervisory control of nonlinear systems with no prior knowledge of noise bounds

The problem of controlling nonlinear noisy systems affected by parametric uncertainties is approached via the introduction of a supervisor which, whenever needed, switches on, in feedback to the plant, a controller selected from a finite set of predesigned controllers. A Lyapunov-based falsification criterion allows one to ensure robust stability in the presence of uncertain constant parameters and exogenous bounded disturbances. Simulations are discussed in order to illustrate the merits of the proposed algorithms.     

Frequency domain identification of Wiener models

This paper proposes a frequency domain algorithm for Wiener model identifications based on exploring the fundamental frequency and harmonics generated by the unknown nonlinearity. The convergence of the algorithm is established in the presence of white noise. No a priori knowledge of the structure of the nonlinearity is required and the linear part can be nonparametric.     

Position synchronization of multiple motion axes with adaptive coupling control

A new control approach to position synchronization of multiple motion axes is developed, by incorporating cross-coupling technology into adaptive control architecture. The control strategy is to stabilize position tracking of each axis while synchronizing its motion with other axes’ motions so that differential position errors amongst axes converge to zero. The proposed adaptive controller and parameter estimator employ coupling control by feeding back position errors and differential position errors, and have been realized to guarantee asymptotic convergence to zero of both position and synchronization errors. Simulations conducted on a multi-axis motion control system demonstrate the effectiveness of the method.     

Motor fluency deficits in the sequencing of actions in schizophrenia.

Many everyday activities depend on the capacity to organize and smoothly execute motor sequences. The authors tested the hypothesis that a sequencing deficit is associated with schizophrenia. They used a new method to distinguish between lower and higher order mechanisms for the impairment. The 1st task involved triggered sequences in which sensory information from 1 movement was the cue for initiation of the following movement. Results showed that the motor sequences were performed as fluently in patients as in controls. The 2nd and 3rd tasks involved sequences in which the entire movement sequence could be preplanned. Patients executed the sequences less fluently than controls but only under the condition where action sequences were required. Furthermore, the patients' fluency deficit increased with sequence complexity. The high discrimination power of Task 3 gave the authors a means to control for a potential psychometric confound involving differential discriminating power and to argue in favor of a specific higher order motor fluency deficit in patients with schizophrenia. It is suggested that basic lower order mechanisms that integrate sensory information with outgoing motor commands are preserved in schizophrenia, whereas higher order integrative mechanisms that are required for the smooth coordination of motor sequences are impaired. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Nonlinear model predictive control with polytopic invariant sets

Ellipsoidal invariant sets have been widely used as target sets in model predictive control (MPC). These sets can be computed by constructing appropriate linear difference inclusions together with additional constraints to ensure that the ellipsoid lies within a given inclusion polytope. The choice of inclusion polytope has a significant effect on the size of the target ellipsoid, but the optimal inclusion polytope cannot in general be computed systematically. This paper shows that use of polytopic invariant sets overcomes this difficulty, allowing larger stabilizable sets without loss of performance. In the interests of online efficiency, consideration is focused on interpolation-based MPC.     

Frequency domain solution to delay-type Nehari problem

This paper generalizes the frequency-domain results on the delay-type Nehari problem in the stable case to the unstable case. The solvability condition of the delay-type Nehari problem is formulated in terms of the nonsingularity of three matrices. The optimal value γ_opt is the maximal γ∈(0,∞) such that one of the three matrices becomes singular. All sub-optimal compensators are parameterized in a transparent structure incorporating a modified Smith predictor.