Flexure control using piezostack actuators: design and implementation

In this paper, the application of high control authority piezostack actuators (PSAs) for active vibration control of large-scale flexible structures is studied. The idea is to add PSAs at appropriate locations of a flexible structure in order to strengthen its stiffness characteristics. In this regard, a flexible link of a macro-micro manipulator system actuated with PSAs is considered. The design of a mechanism for converting the force produced by a PSA to a bending moment is presented and a model for a system consisting of a flexible beam and a PSA is obtained. To this end, the solution of the governing partial differential equation with nonhomogeneous boundary conditions is obtained. Using singular value decomposition of the controllability Grammian of the system, optimum values for actuator parameters are obtained. The experimental results confirm that the suggested method can open up new possibilities in active vibration control of large-scale structures that require a large amount of control authority.     

The functional reanimation of paralyzed limbs.

The functional reanimation of paralyzed limbs has been a longstanding goal of neural prosthetic research, but clinically successful applications have been elusive. Natural voluntary limb movement requires four major elements: actuators (i.e., motor units), sensors (i.e., somatosensory afferents), commands (i.e., cerebral cortical activity), and control (i.e., integration of the previous three elements at various levels of the neuraxis). Prosthetic equivalents of each of these elements are, as yet, primitive and often cumbersome to deploy, but new technologies promise substantial improvements for all. This article focuses on one such technology, bionic neuon (BION) modular microimplants, and its relationship to alternative and complementary technologies. The challenge remains to select and integrate them into systems that can be tailored efficiently to the widely disparate needs of patients with various patterns of weakness and paralysis.     

Empirical models for net-length probability distribution and applications

In this paper, we propose a novel, empirical, and parameterizable model for estimating the probability distribution of wire length for each net in a placed netlist. The model is simple and fast to compute. We did extensive experimentation with state-of-the-art commercial (Cadence) and academic (Parquet and Labyrinth) tools and validated our model. Our distribution model was around three times more accurate than assuming half-perimeter bounding box as the fixed net-length estimate. Since the model is parameterizable it can be easily tailored for different routing tools and benchmarks. This model would be very useful in defining a full fledged probabilistic design automation methodology in which various design metrics are optimized from a probabilistic point of view. We also discuss the application of our model in a novel probabilistic approach to the buffer insertion problem.     

A four-bias three-layer graphene-based THz absorber

Wave absorbers are considered to be fundamental building blocks for the manipulation of light. Almost all optical systems exploit absorbers to realize some functions. A highly tunable wide-band THz absorber is presented herein. Utilizing a dual-bias scheme with a single graphene layer leads to greater freedom to control the absorption response, while a conventional periodic array of graphene ribbons and a layer of graphene sheet are also exploited. Also, a circuit model representation for all the constituent parts of the proposed absorber is developed with an evolved design methodology. According to the simulation results, wide-band absorption from 3.5 to 6 THz is achieved.

     

Extracting Optimal Policies of Hydropower Multi-Reservoir Systems Utilizing Enhanced Differential Evolution Algorithm

Deriving the optimal policies of hydropower multi-reservoir systems is a nonlinear and high-dimensional problem which makes it difficult to achieve the global or near global optimal solution. In order to optimally solve the problem effectively, development of optimization methods with the purpose of optimizing reservoir operation is indispensable as well as inevitable. This paper introduces an enhanced differential evolution (EDE) algorithm to enhance the exploration and exploitation abilities of the original differential evolution (DE) algorithm. The EDE algorithm is first applied to minimize two benchmark functions (Ackley and Shifted Schwefel). In addition, a real world two-reservoir hydropower optimization problem and a large scale benchmark problem, namely ten-reservoir problem, were considered to indicate the effectiveness of the EDE. The performance of the EDE was compared with the original DE to solve the three optimization problems. The results demonstrate that the EDE would have a powerful global ability and faster convergence than the original DE to solve the two benchmark functions. In the 10-reservoir optimization problem, the EDE proved to be much more functional to reach optimal or near optimal solution and to be effective in terms of convergence rate, standard deviation, the best, average and worst values of objective function than the original DE. Also, In the case of two-reservoir system, the best values of the objective function obtained 93.86 and 101.09 for EDE and DE respectively. Based on the results, it can be stated that the most important reason to improve the performance of the EDE algorithm is the promotion of local and global search abilities of the DE algorithm using the number of novel operators. Also, the results of these three problems corroborated the superior performance, the high efficiency and robustness of the EDE to optimize complex and large scale multi-reservoir operation problems.     

On the stability issues of switched singular time‐delay systems with slow switching based on average dwell‐time

The issue of exponential stability analysis of continuous‐time switched singular systems consisting of a family of stable and unstable subsystems with time‐varying delay is investigated in this paper. It is very difficult to analyze the stability of such systems because of the existence of time‐delay and unstable subsystems. In this regard, on the basis of the free‐weighting matrix approach, by constructing the new Lyapunov‐like Krasovskii functional, and using the average dwell‐time approach, delay‐dependent sufficient conditions are derived and formulated in terms of LMIs to check the exponential stability of such systems. This paper also highlights the relationship between the average dwell‐time of the switched singular time‐delay system, its stability, exponential convergence rate of differential states, and algebraic states. Finally, a numerical example is given to confirm the analytical results and illustrate the effectiveness of the proposed strategy. Copyright © 2012 John Wiley & Sons, Ltd.     

Approximating of conic sections by DP curves with endpoint interpolation

Conic sections have many applications in industrial design, however, they cannot be exactly represented in polynomial form. Hence approximating conic sections with polynomials is a challenging problem. In this paper, we use the monomial form of Delgado and Peña (DP) curves and present a matrix representation for them. Using the matrix form and the least squares method, we propose a simple and efficient algorithm for approximating conic sections by DP curves of arbitrary degree with endpoint interpolation. Finally, we test and compare the proposed algorithm on some numerical examples which validates and confirms efficiency of it.     

Safe Autonomous Agent Formation Operations Via Obstacle Collision Avoidance

In this paper, we consider the problem of flocking and shape‐orientation control of multi‐agent systems with inter‐agent and obstacle collision avoidance. We first consider the problem of forcing a set of autonomous agents to form a desired formation shape and orientation while avoiding inter‐agent collision and collision with convex obstacles, and following a trajectory known to only one of the agents, namely the leader of the formation. Then we build upon the solution given to this problem and solve the problem of guaranteeing obstacle collision avoidance by changing the size and the orientation of the formation. Changing the size and the orientation of the formation is helpful when the agents want to go through a narrow passage while the existing size or orientation of the formation does not allow this. We also propose collision avoidance algorithms that temporarily change the shape of the formation to avoid collision with stationary or moving nonconvex obstacles. Simulation results are presented to show the performance of the proposed control laws.     

Short‐Time Linear Quadratic Form Technique for Estimating Fast‐Varying Parameters in Feedback Loops

The precision of a closed‐loop controller system designed for an uncertain plant depends strongly upon the maximum extent to which it is possible to track the trend of time‐varying parameters of the plant. The aim of this study is to describe a new parameter estimation algorithm that is able to follow fast‐varying parameters in closed‐loop systems. The short‐time linear quadratic form (STLQF) estimation algorithm introduced in this paper is a technique for tracking time‐varying parameters based on short‐time analysis of the regressing variables in order to minimize locally a linear quadratic form cost function. The established cost function produces a linear combination of errors with several delays. To meet this objective, mathematical development of the STLQF estimation algorithm is described. To implement the STLQF algorithm, the algorithm is applied to a planar mobile robot with fast‐varying parameters of inertia and viscous and coulomb frictions. Next, performance of the proposed algorithm is assessed against noise effects and variation in the type of parameters.