• International Journal of Precision Engineering and Manufacturing
• /
• v.2 no.4
• /
• pp.61-68
• /
• 2001

A new approach for motion control of constrained mechanical systems is proposed in this paper. The approach uses a new equations of motion which is proposed by Udwadia and Kalaba and named Udwadia-Kalaba's equations of motion in this paper. This paper reveals that the Udwadia-Kalaba's equations of motion is more adequate to model constrained mechanical systems rather than the famous Lagrange's equations of motion at least for control purpose. The proposed approach coverts most of constraints including holonomic and nonholonomic constraints. Comparison of simulation results of two systems which are well-known in the literature show the superiority of the proposed approach. Furthermore, a special constrained mechanical system which includes nonlinear generalized velocities in its constraint equations, which has been considered to be difficult to control, can be controlled easily. It shows the possibility of the proposed approach to being a general framework for motion control of constrained mechanical systems with various kinds of constraints.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2495-2497
• /
• 2000

Level control in the steam generator of a nuclear power plant is important process. But, the low power operation of nuclear power plant causes nonlinear characteristics and non minimum phase characteristics (swell and shrink), change of delay. So, we can't lead good results with conventional PID controller. Particularly, the design of controller with constraints is necessary. This paper introduces MPC(Model Predictive Control) with constraints and designs a good performance MPC controller in spite of the input constraints and nonlinear characteristics, non-minimum phase characteristics

• Bulletin of the Korean Mathematical Society
• /
• v.30 no.1
• /
• pp.1-7
• /
• 1993

Vector optimization problems consist of two or more objective functions and constraints. Optimization entails obtaining efficient solutions. Geoffrion [3] introduced the definition of the properly efficient solution in order to eliminate efficient solutions causing unbounded trade-offs between objective functions. In 1974, Isermann [7] obtained a necessary and sufficient condition for an efficient solution of a linear vector optimization problem with linear constraints and showed that every efficient solution is a properly efficient solution. Since then, many authors [1, 2, 4, 5, 6] have extended the Isermann's results. In particular, Gulati and Islam [4] derived a necessary and sufficient condition for an efficient solution of a linear vector optimization problem with nonlinear constraints, under certain assumptions. In this paper, we consider the following nonlinear vector optimization problem (NVOP): (Fig.) where for each i, f$_{i}$ is a differentiable function from R$^{n}$ into R and g is a differentiable function from R$^{n}$ into R$^{m}$ .

• Computational Structural Engineering
• /
• v.9 no.3
• /
• pp.179-186
• /
• 1996

A simple nonlinear programming(NLP) formulation for the optimal topology problem of structures is developed and examined. The NLP formulation is general, and can handle arbitrary objective functions and arbitrary stress, displacement constraints under multiple loading conditions. The formulation is based on simultaneous analysis and design approach to avoid stiffness matrix singularity resulting from zero sizing variables. By embedding the equilibrium equations as equality constraints in the nonlinear programming problem, we avoid constructing and factoring a system stiffness matrix, and hence avoid its singularity. The examples demonstrate that the formulation is effective for finding an optimal solution, and shown to be robust under a variety of constraints.

• Structural Engineering and Mechanics
• /
• v.58 no.3
• /
• pp.555-576
• /
• 2016

In this paper an efficient approach is introduced for design and analysis of double-layer grids including both geometrical and material nonlinearities, while the results are compared with those considering material nonlinearity. Optimum design procedure based on Enhanced Colliding Bodies Optimization method (ECBO) is applied to optimal design of two commonly used configurations of double-layer grids. Two ranges of spans as small and big sizes with certain bays of equal length in two directions are considered for each type of square grids. ECBO algorithm obtains minimum weight grid through appropriate selection of tube sections available in AISC Load and Resistance Factor Design (LRFD). Strength constraints of AISC-LRFD specifications and displacement constraints are imposed on these grids.

• International Journal of Aeronautical and Space Sciences
• /
• v.16 no.2
• /
• pp.264-277
• /
• 2015

This article investigates various transcription techniques for the Legendre pseudospectral (PS) method to compare the pros and cons of each approach. Eight combinations from four different types of collocation points and two discretization methods for dynamic constraints, which differentiate Legendre PS transcription techniques, are implemented to solve a carefully selected test set of nonlinear optimal control problems (NOCPs). The convergence property and prediction accuracy are compared to provide a useful guideline for selecting the best combination. The tested NOCPs consist of the minimum time, minimum energy, and problems with state and control constraints. Therefore, the results drawn from this comparative study apply to the solution of similar types of NOCPs and can mitigate much debate about the best combinations. Additionally, important findings from this study can be used to improve the numerical efficiency of the Legendre PS methods. Three PS applications to the aerospace engineering problems are demonstrated to prove this point.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.2
• /
• pp.277-284
• /
• 2018

In this paper, a new numerical method of finding the roots of a nonlinear system is proposed, which extends the conventional fixed point iterative method by relaxing the constraints on it. The proposed method determines the real valued roots and expands the convergence region by relaxing the constraints on the conventional fixed point iterative method, which transforms the diverging root searching iterations into the converging iterations by employing the metric induced by the geometrical characteristics of a polynomial. A metric is set to measure the distance between a point of a real-valued function and its corresponding image point of its inverse function. The proposed scheme provides the convenience in finding not only the real roots of polynomials but also the roots of the nonlinear systems in the various application areas of science and engineering.

• Bulletin of the Korean Mathematical Society
• /
• v.50 no.3
• /
• pp.823-832
• /
• 2013

We present a new algorithm for solving a system of nonlinear equations with convex constraints which combines proximal point and projection methodologies. Compared with the existing projection methods for solving the problem, we use a different system of linear equations to obtain the proximal point; and moreover, at the step of getting next iterate, our projection way and projection region are also different. Based on the Armijo-type line search procedure, a new hyperplane is introduced. Using the separate property of hyperplane, the new algorithm is proved to be globally convergent under much weaker assumptions than monotone or more generally pseudomonotone. We study the convergence rate of the iterative sequence under very mild error bound conditions.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.11 no.2
• /
• pp.222-233
• /
• 1987

A dynamic modeling procedure for developing a control model of the driving system of a heavy industrial vehicle is presented. The dynamic model is derived by applying generalized Lagrangian equations to each component of the system and imposing kinematic relations between components as constraints. In order to obtain the control model, a few assumptions are made for the simplification of the nonlinear and complicated model, which is justified by the comparison of the simulation results of the original full nonlinear model and the simplified control model.

• Journal of applied mathematics & informatics
• /
• v.19 no.1_2
• /
• pp.215-229
• /
• 2005

In this paper, constraint aggregation is combined with the adjoint and multiple shooting strategies for optimal control of differential algebraic equations (DAE) systems. The approach retains the inherent parallelism of the conventional multiple shooting method, while also being much more efficient for large scale problems. Constraint aggregation is employed to reduce the number of nonlinear continuity constraints in each multiple shooting interval, and its derivatives are computed by the adjoint DAE solver DASPKADJOINT together with ADIFOR and TAMC, the automatic differentiation software for forward and reverse mode, respectively. Numerical experiments demonstrate the effectiveness of the approach.