Maximization of eigenvalues using topology optimization

Topology optimization is used to optimize the eigenvalues of plates. The results are intended especially for MicroElectroMechanical Systems (MEMS) but can be seen as more general. The problem is not formulated as a case of reinforcement of an existing structure, so there is a problem related to localized modes in low density areas. The topology optimization problem is formulated using the SIMP method. Special attention is paid to a numerical method for removing localized eigenmodes in low density areas. The method is applied to numerical examples of maximizing the first eigenfrequency. One example is a practical MEMS application; a probe used in an Atomic Force Microscope (AFM). For the AFM probe the optimization is complicated by a constraint on the stiffness and constraints on higher order eigenvalues. Received June 10, 1999     

Dexterous workspace optimization of an asymmetric six-degree of freedom Stewart–Gough platform type manipulator

In this paper, an asymmetric Generalized Stewart–Gough Platform (GSP) type parallel manipulator is designed by considering the type synthesis approach. The asymmetric six-Degree Of Freedom (DOF) manipulator optimized in this paper is selected among the GSPs classified under the name of 6D. The dexterous workspace optimization of Asymmetric parallel Manipulator with tEn Different Linear Actuator Lengths (AMEDLAL) subject to kinematics and geometric constraints is performed by using the Particle Swarm Optimization (PSO). The condition number and Minimum Singular Value (MSV) of homogenized Jacobian matrix are employed to obtain the dexterous workspace of AMEDLAL. Finally, the six-DOF AMEDLAL is also compared with the optimized Traditional Stewart–Gough Platform Manipulator (TSPM) considering the volume of the dexterous workspace in order to demonstrate its kinematic performance. Comparisons show that the manipulator proposed in this study illustrates better kinematic performance than TSPM.     

Simultaneous cognitive origin of life and information

Shannon’s information quantity I(E) = log(1/P(E)) is defined under an assumption of the existence of a “cognitive subjective entity” capable of judging yes/no or occurred/not-occurred of an event E (which occurs with a probability P(E)). The final acceptor/user of information is a living individual, although first and/or intermediate sender(s) and/or acceptor(s) of information may be either living individual(s) or nonliving element(s) or man-made machine(s). Therefore we can conclude that information is a most essential character of living individuals, and that information and life must have emerged simultaneously as a “minimum cognitive system” (MCS). Since then, living individuals/lives must have evolved as “self-revising learning neural network machines” capable of “active evolution”. How MCS could have emerged was discussed.     

The inheritance of BDE-property in sharply dominating lattice effect algebras and (o)-continuous states

We study remarkable sub-lattice effect algebras of Archimedean atomic lattice effect algebras E, namely their blocks M, centers C(E), compatibility centers B(E) and sets of all sharp elements S(E) of E. We show that in every such effect algebra E, every atomic block M and the set S(E) are bifull sub-lattice effect algebras of E. Consequently, if E is moreover sharply dominating then every atomic block M is again sharply dominating and the basic decompositions of elements (BDE of x) in E and in M coincide. Thus in the compatibility center B(E) of E, nonzero elements are dominated by central elements and their basic decompositions coincide with those in all atomic blocks and in E. Some further details which may be helpful under answers about the existence and properties of states are shown. Namely, we prove the existence of an (o)-continuous state on every sharply dominating Archimedean atomic lattice effect algebra E with B(E)\not = C(E).B(E)\not =C(E). Moreover, for compactly generated Archimedean lattice effect algebras the equivalence of (o)-continuity of states with their complete additivity is proved. Further, we prove “State smearing theorem” for these lattice effect algebras.     

Trace monoids with idempotent generators and measure-only quantum automata

In this paper, we analyze a model of 1-way quantum automaton where only measurements are allowed ( MON -1qfa). The automaton works on a compatibility alphabet (S, E)(\Sigma, E) of observables and its probabilistic behavior is a formal series on the free partially commutative monoid FI(S, E)\hbox{FI}(\Sigma, E) with idempotent generators. We prove some properties of this class of formal series and we apply the results to analyze the class LMO(S, E){\bf LMO}(\Sigma, E) of languages recognized by MON -1qfa’s with isolated cut point. In particular, we prove that LMO(S, E){\bf LMO}(\Sigma, E) is a boolean algebra of recognizable languages with finite variation, and that LMO(S, E){\bf LMO}(\Sigma, E) is properly contained in the recognizable languages, with the exception of the trivial case of complete commutativity.     

Connecting Polygonizations via Stretches and Twangs

We show that the space of polygonizations of a fixed planar point set S of n points is connected by O(n ²) “moves” between simple polygons. Each move is composed of a sequence of atomic moves called “stretches” and “twangs,” which walk between weakly simple “polygonal wraps” of S. These moves show promise to serve as a basis for generating random polygons.     

Optimal trajectory generation algorithm for serial and parallel manipulators

In this paper, an Optimal Trajectory Generation Algorithm (OTGA) is developed for generating minimum-time smooth motion trajectories for serial and parallel manipulators. OTGA is divided into two phases. The first phase encompasses derivation of minimum-time optimal trajectory using cubic spline due to its less vibration and overshoot characteristics. Although cubic splines are widely used in robotics, velocity and acceleration ripples in the first & last knots can worsen manipulator trajectory. The second phase includes changing cubic spline interpolation in the first and last knots of optimized trajectory with 7th order polynomial for having zero jerk at the beginning and end points of trajectory. Performing this modification eliminate undesired worsening in the trajectory and provide smoother start and stop of joint motions. Particle Swarm Optimization (PSO) is chosen as optimization algorithm because of its easy implementation and successful optimization performance. OTGA has been tested in simulation for PUMA robot and results are compared with algorithms proposed by earlier authors. In addition, a discrete-time PID control scheme for PUMA robot is designed for comparing energy consumption of OTGA with algorithms developed by previous authors. Comparison results illustrated that OTGA is the better trajectory generation algorithm than the others.     

Maintenance of a Piercing Set for Intervals with Applications

   Abstract. We show how to maintain efficiently a minimum piercing set for a set S of intervals on the line, under insertions and deletions to/from S. A linear-size dynamic data structure is presented, which enables us to compute a new minimum piercing set following an insertion or deletion in time O(c( S) log |S|), where c (S) is the size of the new minimum piercing set. We also show how to maintain a piercing set for S of size at most (1+ɛ)c (S), for 0 < ɛ ≤ 1 , in

Correlation between the gradients of the quadratic functional and its clipped prototype

Applicability of clipping of quadratic functional E = −0.5x ⁺ Tx + Bx in the minimization problem is considered (here x is the configurational vector and B ∈ R ^N is real valued vector). The probability that the gradient of this functional and the gradient of clipped functional ɛ = −0.5x ⁺ τx + bx are collinear is shown to be very high (the matrix τ is obtained by clipping of original matrix T: τ_ij = sgnT _ij ). It allows the conclusion that minimization of functional ɛ implies minimization of functional E. We can therefore replace the laborious process of minimizing functional E by the minimization of its clipped prototype ɛ. Use of the clipped functional allows sixteen-times reduction of the computation time and computer memory usage.     

Sequential approximate optimization using dual subproblems based on incomplete series expansions

In this paper, dual formulations for nonlinear multipoint approximations with diagonal approximate Hessian matrices are proposed; these approximations for example derive from the incomplete series expansion (ISE) proposed previously. A salient feature of the ISE is that it may be used to formulate strictly convex and separable (recast) primal approximate subproblems for use in sequential approximate optimization (SAO). In turn, this allows for the formulation of highly efficient dual formulations, and different combinations of direct, reciprocal, and exponential intervening variables for the objective and the constraint functions may be used. Two frequently encountered problems in structural optimization, namely the weight minimization problem with sizing design variables and the minimum compliance topology optimization problem, are degenerate cases of the formulations we present. Computational experiments confirm the efficiency of our proposed methodology; to this end, comparative results for the method of moving asymptotes (MMA) are presented. Based on the paper entitled “Duality in Convex Nonlinear Multipoint Approximations with Diagonal Approximate Hessian Matrices Deriving from Incomplete Series Expansions,” presented at the 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Portsmouth, VA, USA, September 2006, paper no. AIAA-2006-7090.