Positive invariant set estimation of adaptive controller in the presence of input saturation

For a class of linear dynamical systems with constant unknown parameters, an adaptive control scheme is developed that provides stable adaptation in the presence of input magnitude constraints. Whereas for open‐loop stable systems the results are global, for open‐loop unstable systems, the problem of nonconservative estimation of the nonempty positive invariant set is cast into an LMI framework, which can be efficiently solved numerically via convex optimization. To achieve this, a standard result toward invariant set characterization is appropriately extended to accommodate bounded disturbance and model uncertainties. In addition to closed‐loop stability, performance bounds of the adaptive closed‐loop system are analyzed, and the degradation due to the possible control deficiency is quantified. Simulation examples of aerospace applications are included to illustrate the proposed method. Copyright © 2012 John Wiley & Sons, Ltd.     

Effects of foot placement,hand positioning,age and climbing biodynamics on ladder slip outcomes

Ladder falls frequently cause severe injuries; yet the factors that influence ladder slips/falls are not well understood. This study aimed to quantify (1) the effects of restricted foot placement, hand positioning, climbing direction and age on slip outcomes, and (2) differences in climbing styles leading to slips versus styles leading to non-slips. Thirty-two occupational ladder users from three age groups (18–24, 25–44 and 45–64 years) were unexpectedly slipped climbing a vertical ladder, while being assigned to different foot placement conditions (unrestricted vs. restricted toe clearance) and different hand positions (rails vs. rungs). Constraining foot placement increased the climber's likelihood of slipping (p < 0.01), while younger and older participants slipped more than the middle-aged group (p < 0.01). Longer double stance time, dissimilar and more variable foot and body positioning were found in styles leading to a slip. Maintaining sufficient toe clearance and targeting ladder safety training to younger and older workers may reduce ladder falls.

Practitioner Summary: Ladder falls frequently cause severe occupational fall injuries. This study aims to identify safer ladder climbing techniques and individuals at risk of falling. The results suggest that ladders with unrestricted toe clearance and ladder climbing training programmes, particularly for younger and older workers, may reduce ladder slipping risk.     

Novel L1 neural network adaptive control architecture with guaranteed transient performance.

In this paper, we present a novel neural network (NN) adaptive control architecture with guaranteed transient performance. With this new architecture, both input and output signals of an uncertain nonlinear system follow a desired linear system during the transient phase, in addition to stable tracking. This new architecture uses a low-pass filter in the feedback loop, which consequently enables to enforce the desired transient performance by increasing the adaptation gain. For the guaranteed transient performance of both input and output signals of the uncertain nonlinear system, the L1 gain of a cascaded system, comprised of the low-pass filter and the closed-loop desired reference model, is required to be less than the inverse of the Lipschitz constant of the unknown nonlinearities in the system. The tools from this paper can be used to develop a theoretically justified verification and validation framework for NN adaptive controllers. Simulation results illustrate the theoretical findings.     

Geometry of Pursuit-Evasion on Second Order Rotation Surfaces

Differential games with simple motionin a game space with non-unique shortest geodesic line havephase portraits with complicated structure of singular surfaces.The successful solution of such games on a family of two-dimensionalcones [1] was based to the large extent on the parameter analysisof the problem. In the present paper the results of pursuit gameon a cone of one sheet are extended to the game on the full two-sheetcone. The latter surface is included in one-parametric familyof rotation surfaces (each of which is characterized by two moreparameters), and the game on it is considered as the generatingproblem for the analysis of the games on the perturbed surfaces.The paper continues the previous investigations of the authors.In [2], [3] some local results are obtained for the games onRiemannian manifolds. In [1], [2] the game problems are solvedfor a two-dimensional cone, in [4], [5] one sheet of a double-sheetedrotation hyperboloid is considered as game space and geometricalproperties of trajectories are analyzed.     

Does Culturally Adapted Online Communication Work? A Study of American and Chinese Internet Users’ Attitudes and Preferences Toward Culturally Customized Web Design Elements

Various scholars have argued that today's multicultural online marketplace necessitates cultural adaptation of Web communications. This argument has largely been based on the assumption that culture, as a source of acceptable norms and behaviors, influences online expectations, preferences, and experiences. Few, however, have questioned the validity of this assumption. Our study aims to fill that gap. It examines whether Internet users' cultural backgrounds are reflected in the attitudes toward Web design elements. A survey of American and Chinese Internet users and a content analysis revealed that cultural backgrounds play a substantial role in determining Web design preferences and attitudes. The findings of this study represent an important step in developing and validating a framework that international marketers can use to customize Web sites and improve targeting in online environment. The findings also suggest that cultural customization of online communication is particularly effective when users have strong ethnic identities.     

Adaptive output feedback control of a class of non-linear systems using neural networks

This paper presents tools for the design of a neural network based adaptive output feedback controller for a class of partially or completely unknown non-linear multi-input multi-output systems without zero dynamics. Each of the outputs is assumed to have relative degree less or equal to 2. A neural network based adaptive observer is designed to estimate the derivatives of the outputs. Subsequently, the adaptive observer is integrated into a neural network based adaptive controller architecture. Conditions are derived which guarantee the ultimate boundedness of all the errors in the closed loop system. Stability analysis reveals simultaneous learning rules for both the adaptive neural network observer and adaptive neural network controller. The design approach is illustrated using a fourth order two-input two-output example, in which each output has relative degree two.     

Decentralized adaptive output feedback control via input/output inversion

A decentralized adaptive output feedback control design method is presented for control of large-scale interconnected systems. It is assumed that all the controllers share prior information about the subsystem reference models. Based on that information, a linear dynamic output feedback compensator and linearly parameterized neural network (NN) are introduced for each subsystem to partially cancel the effect of the interconnections on the tracking performance. Boundedness of error signals is shown through Lyapunov's direct method.     

On initial value and terminal value problems for Hamilton–Jacobi equation

First order partial differential equations (PDE) are often the main tool to model problems in optimal control, differential games, image processing, physics, etc. Dependent upon the particular application, the boundary conditions are specified either at the initial time instant, leading to an initial value problem (IVP), or at the terminal time instant, leading to a terminal value problem (TVP). The IVP and TVP have in general different solutions. Thus introducing a new model in terms of a first order PDE one has to consider both possibilities of IVP and TVP, unless there is a direct physical indication. In this paper we also particularly answer the following question: how should the initial value at the initial surface and the terminal value at the terminal surface be coordinated in order to generate the same solution? One may expect that for a given initial value the consistent terminal value is the value of the IVP solution at the terminal surface. The second (time-varying) example in this paper shows that, generally, this is not true for non-smooth initial conditions. We discuss also the difference between the IVP and TVP formulations, the connection between the Hamiltonians arising in IVP and TVP.     

Neural network adaptive output feedback control for intensive care unit sedation and intraoperative anesthesia.

The potential applications of neural adaptive control for pharmacology, in general, and anesthesia and critical care unit medicine, in particular, are clearly apparent. Specifically, monitoring and controlling the depth of anesthesia in surgery is of particular importance. Nonnegative and compartmental models provide a broad framework for biological and physiological systems, including clinical pharmacology, and are well suited for developing models for closed-loop control of drug administration. In this paper, we develop a neural adaptive output feedback control framework for nonlinear uncertain nonnegative and compartmental systems with nonnegative control inputs. The proposed framework is Lyapunov-based and guarantees ultimate boundedness of the error signals. In addition, the neural adaptive controller guarantees that the physical system states remain in the nonnegative orthant of the state space. Finally, the proposed approach is used to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for noncardiac surgery.