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This paper presents adaptive neural tracking control for a class of uncertain single-input single-output (SISO) non-affine nonlinear systems in general form. To deal with the non-affine appearance of the control variables, the Taylor series expansion is employed to transform the systems into a block-triangular affine form in the neighborhood of the ideal unknown control law. The developed neural control...
This paper proposes a novel approach to phase-noise compensation. The basic idea is to approximate the phase-noise statistics by a finite number of realizations, i.e., a phase-noise codebook. The receiver then uses an augmented received signal model, where the codebook index is estimated along with other parameters. The realization of the basic idea depends on the details of the air interface, the...
This paper proposes an algorithmic modeling and analysis method to study the dynamics of nonlinear biological systems. Motivated by the recent use of piecewise affine models in reachability analysis of continuous dynamical systems, we propose a multi-affine approximation method to study biological system models defined on hyperrectangle. We show that such approximation is useful for constructing system's...
This paper focusses on the strange nature and qualitative behavior associated with the systems characterized by State Dependent-Delay Differential Equations (SD-DDEs). We consider one of the most simple and innocently looking SD-DDEs x(t) = ±x(t-x(t)). This retarded SD-DDE brings a lot of intricacies. It looks linear but is actually a nonlinear SD-DDE in disguise. It exhibits the phenomenon of bifurcation...
We present an algorithm for resampling data from a non-uniform grid onto a uniform grid. Our algorithm termed generalized sparse uniform resampling (GSURS) uses methods from modern sampling theory. Selection of an intermediate subspace generated by integer translations of a compactly supported generating kernel produces a sparse system of equations representing the relation between the nonuniformly...
Parametric filters, such as the Extended Kalman Filter and the Unscented Kalman Filter, typically scale well with the dimensionality of the problem, but they are known to fail if the posterior state distribution cannot be closely approximated by a density of the assumed parametric form.
This paper deals with the generation of motion for complex dynamical systems (such as humanoid robots) to achieve several concurrent objectives. Hierarchy of tasks and optimal control are two frameworks commonly used to this aim. The first one specifies control objectives as a number of quadratic functions to be minimized under strict priorities. The second one minimizes an arbitrary user-defined...
This paper reformulates an optimization algorithm previously presented in continuous-time to one using structured integration and structured linearization methods from discrete mechanics. The objective is to synthesize trajectories for dynamic robotic systems that improve the estimation of model parameters by using a metric on Fisher information in a nonlinear projection-based trajectory optimization...
What is it that makes movement around obstacles hard? The answer seems clear: obstacles contort the geometry of the workspace and make it difficult to leverage what we consider easy and intuitive straight-line Cartesian geometry. But is Cartesian motion actually easy? It's certainly well-understood and has numerous applications. But beneath the details of linear algebra and pseudoinverses, lies a...
Ensuring safety in partially-known environments is a critical problem in robotics since the environment is perceived through sensors and the environment cannot be completely known ahead of time. Prior work has considered the problem of finding positive control invariant sets (PCIS). However, this approach limits the planning horizon of the motion planner since the PCIS must lie completely in the limited...
A vision-based enhanced PID control algorithm for the gap-flying-through problem using a low-cost multirotor platform is the main topic of this paper. We designed an image processing program to detect the target rectangle gap in each video frame captured by onboard camera of the drone. During the process, some manipulation such as dilate and erode are implemented to reduce the noise. To control the...
This paper deals with the control of a two-degree-of-freedom, laboratory-scale helicopter-like system (termed the toycopter), where the aerodynamic force is manipulated using the propeller speed. This system can be shown not to be flat and thus classical linearization techniques cannot be applied. However, a low-order flat system can be obtained by (i) using a high-gain feedback with suitable proportional...
A systematic procedure for planning sensor movements in a specified spatial domain in such a way as to maximize the accuracy of parameter estimation of a given distributed system is proposed. The global design criterion is the expectation of a general local design criterion defined on the Fisher information matrix, given a-priori distribution of the parameters to be identified. The approach converts...
Switched linear systems exhibit a continuous state evolving along the continuous flow of time according to linear time invariant differential equations. Furthermore, a discrete interface to the environment is provided, acting on input signals by switching between a finite number of differential equations and generating output signals when the continuous state crosses certain boundaries. We suggest...
The determination of the reachable states for a class of infinite-dimensional nonlinear systems with control constraints is investigated. The main results reduce this problem to the determination of the reachable states, by means of admissible controls, for the approximate linear systems. The approach is developed using a state space system framework and is based on the application of a result from...
Neural networks can be used as continuous-time models of nonlinear dynamic systems. Based on the neural plant model, various nonlinear control design methodologies may be applied. In this study, direct inverse control and input-output-linearization are used for trajectory tracking of a batch reactor. Given the same approximate neural model, input-output-linearization proves to be superior to direct...
The aim of this paper is to provide a methodology for the design of practical continuous high gain event-based observers for nonlinear systems with an almost everywhere injective r-observability map. As opposed to other high gain approaches, injectivity is allowed to be lost for a nonempty set of bad input points. An example with simulations illustrates the procedure.
The solution to constrained linear model predictive control (MPC) problems can be pre-computed off-line in an explicit form as a piecewise affine (PWA) state feedback law defined on polyhedral regions of the state space. Even though real-time optimization is avoided, implementation of the PWA state-feedback law may still require a significant amount of computation due to the problem of determining...
We introduce in this paper the Random Exchange Diffusion Bernoulli Filter (RndEx-BF), which enables joint target detection and tracking by a network of collaborative sensors. RndEx-BF is a fully distributed algorithm that, unlike consensus-based solutions, does not require iterative internode communication between sensor measurements. Internode communication cost is further reduced by a novel hybrid...
The particle Gibbs algorithm can be used for Bayesian parameter estimation in Markovian state space models. Sometimes the resulting Markov chains mix slowly when the component particle filter suffers from degeneracy. This effect can be somewhat alleviated using backward simulation. In this paper we show how a simple modification to this scheme, which we refer to as refreshed backward simulation, can...
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