Index-1 Differential-algebraic Equations Research Articles

On solving optimal control problems with higher index differential-algebraic equations

This paper deals with optimal control problems described by higher index differential-algebraic equations (DAEs). We introduce a numerical procedure for solving these problems. The procedure has the following features: it is based on the appropriately defined adjoint equations formulated for the discretized system equations; system equations are discretized by an implicit Runge–Kutta method; initialization for higher index DAEs is performed with the help of Pantelides’ algorithm. Our approach to optimal control problems does not require differentiation of some algebraic equations in order to transform the system to ordinary differential equations. This paper presents numerical examples related to index 3 DAEs showing the validity of the proposed approach.

Reachability Analysis of Nonlinear Differential-Algebraic Systems

This paper presents a numerical procedure for the reachability analysis of systems with nonlinear, semi-explicit, index-1 differential-algebraic equations. The procedure computes reachable sets for uncertain initial states and inputs in an overapproximative way, i.e. it is guaranteed that all possible trajectories of the system are enclosed. Thus, the result can be used for formal verification of system properties that can be specified in the state space as unsafe or goal regions. Due to the representation of reachable sets by zonotopes and the use of highly scalable operations on them, the presented approach scales favorably with the number of state variables. This makes it possible to solve problems of industry-relevant size, as demonstrated by a transient stability analysis of the IEEE 14-bus benchmark problem for power systems.

Variable step 2-point block backward differentiation formula for index-1 differential algebraic equations

In this paper, index-1 differential algebraic equations have been solved via a block backward differentiation formula (BDF) using variable step size. Two solution values are obtained simultaneously based on the method in the block. The strategy of controlling the step size is proposed. The method is compared with the existing variable step BDF method. Numerical results are given to support the enhancement of the method in terms of accuracy.

Robustness of stability of time-varying index-1 DAEs

We study exponential stability and its robustness for time-varying linear index-1 differential-algebraic equations. The effect of perturbations on the leading coefficient matrix is investigated. An appropriate class of allowable perturbations is introduced. Robustness of exponential stability with respect to a certain class of perturbations is proved in terms of the Bohl exponent and perturbation operator. Finally, a stability radius involving these perturbations is introduced and investigated. In particular, a lower bound for the stability radius is derived. The results are presented by means of illustrative examples.

Indirect Solution of Inequality Constrained and Singular Optimal Control Problems Via a Simple Continuation Method

This paper develops a simple continuation method for the approximate solution of optimal control problems. The class of optimal control problems considered include (i) problems with bounded controls, (ii) problems with state variable inequality constraints (SVIC), and (iii) singular control problems. The method used here is based on transforming the state variable inequality constraints into equality constraints using nonnegative slack variables. The resultant equality constraints are satisfied approximately using a quadratic loss penalty function. Similarly, singular control problems are made nonsingular using a quadratic loss penalty function based on the control. The solution of the original problem is obtained by solving the transformed problem with a sequence of penalty weights that tends to zero. The penalty weight is treated as the continuation parameter. The paper shows that the transformed problem yields necessary conditions for a minimum that can be written as a boundary value problem involving index-1 differential–algebraic equations (BVP-DAE). The BVP-DAE includes the complementarity conditions associated with the inequality constraints. It is also shown that the necessary conditions for optimality of the original problem and the transformed problem differ by a term that depends linearly on the algebraic variables in the DAE. Numerical examples are presented to illustrate the efficacy of the proposed technique.

A Stable Inversion Method for Feedforward Control of Constrained Flexible Multibody Systems

The inverse dynamics of flexible multibody systems is formulated as a two-point boundary value problem for an index-3 differential-algebraic equation (DAE). This DAE represents the equation of motion with kinematic and trajectory constraints. For so-called nonminimum phase systems, the remaining dynamics of the inverse model is unstable. Therefore, boundary conditions are imposed not only at the initial time but also at the final time in order to obtain a bounded solution of the inverse model. The numerical solution strategy is based on a reformulation of the DAE in index-2 form and a multiple shooting algorithm, which is known for its robustness and its ability to solve unstable problems. The paper also describes the time integration and sensitivity analysis methods that are used in each shooting phase. The proposed approach does not require a reformulation of the problem in input-output normal form, which is known from nonlinear control theory. It can deal with serial and parallel kinematic topology, minimum phase and nonminimum phase systems, and rigid and flexible mechanisms.

On the Gröbner basis triangularization of constraint equations in natural coordinates

Efficient dynamic simulation code is essential in many situations (including hardware-in-the-loop and model-predictive control applications), and highly beneficial in others (such as design optimization, sensitivity analysis, parameter identification, and controller tuning tasks). When the number of modeling coordinates n exceeds the degrees-of-freedom of the system f, as is often the case when closed kinematic chains are present, the governing dynamic equations consist of n second-order ordinary differential equations (ODEs) coupled with m=n−f algebraic constraint equations. This set of n+m index-3 differential-algebraic equations can be difficult to solve in an efficient yet accurate manner. Embedding (or generalized coordinate partitioning) can be used to obtain f ODEs (one for each independent acceleration), which are generally more amenable to numerical integration; however, the dependent positions are typically computed from the independent positions at each time step. Newton–Raphson iteration is often used for solving the position-level kinematics, but only provides solutions to within a specified tolerance, and can require several iterations to converge. In this work, Grobner bases are used to obtain recursively solvable symbolic solutions for the dependent positions, which can then be evaluated to within machine precision using a fixed number of arithmetic operations. Natural coordinates are particularly attractive in this context, since the resulting constraint equations are maximally quadratic polynomials and are, therefore, easily triangularized. The proposed approach is suitable for use in an automated formulation procedure and, as demonstrated by three examples, is capable of generating highly efficient simulation code with minimal additional effort required at the formulation stage.

Parameter identification for multibody systems expressed in differential-algebraic form

The ability of a multibody dynamic model to accurately predict the response of a physical system relies heavily on the use of appropriate system parameters in the mathematical model. Thus, the identification of unknown system parameters (or parameters that are known only approximately) is of fundamental importance. If experimental measurements are available for a mechanical system, the parameters in the corresponding mathematical model can be identified by minimizing the error between the model response and the experimental data. Existing work on parameter estimation using linear regression requires the elimination of the Lagrange multipliers from the dynamic equations to obtain a system of ordinary differential equations in the independent coordinates. The elimination of the Lagrange multipliers may be a nontrivial task, however, as it requires the assembly of an orthogonal complement of the Jacobian. In this work, we present an approach to identify inertial system parameters and Lagrange multipliers simultaneously by exploiting the structure of the index-3 differential-algebraic equations of motion.

Index-aware model order reduction for differential-algebraic equations

We introduce a model order reduction (MOR) procedure for differential-algebraic equations, which is based on the intrinsic differential equation contained in the starting system and on the remaining algebraic constraints. The decoupling procedure in differential and algebraic part is based on the projector and matrix chain which leads to the definition of tractability index. The differential part can be reduced by using any MOR method, we use Krylov-based projection methods to illustrate our approach. The reduction on the differential part induces a reduction on the algebraic part. In this paper, we present the method for index-1 differential-algebraic equations. We implement numerically this procedure and show numerical evidence of its validity.

Global unique solvability for memristive circuit DAEs of Index 1

AbstractKnown solvability results for nonlinear index‐1 differential‐algebraic equations (DAEs) are in general local and rely on the Implicit Function Theorem. In this paper, we derive a global result which guarantees unique solvability on a given time interval for a certain class of index‐1 DAEs with certain monotonicity conditions. Based on this result, we show that memristive circuit DAEs arising from the modified nodal analysis are uniquely solvable if they fulfill certain passivity and network topological conditions.Furthermore we present an error estimation for the solution with respect to perturbations on the right‐hand side and in the initial value. Copyright © 2013 John Wiley & Sons, Ltd.

Parallel indirect solution of optimal control problems

SUMMARY This paper presents an algorithm for the indirect solution of optimal control problems that contain mixed state and control variable inequality constraints. The necessary conditions for optimality lead to an inequality constrained two-point BVP with index-1 differential-algebraic equations (BVP-DAEs). These BVP-DAEs are solved using a multiple shooting method where the DAEs are approximated using a single-step linearly implicit Runge–Kutta (Rosenbrock–Wanner) method. An interior-point Newton method is used to solve the residual equations associated with the multiple shooting discretization. The elements of the residual equations, and the Jacobian of the residual equations, are constructed in parallel. The search direction for the interior-point method is computed by solving a sparse bordered almost block diagonal (BABD) linear system. Here, a parallel-structured orthogonal factorization algorithm is used to solve the BABD system. Examples are presented to illustrate the efficiency of the parallel algorithm. It is shown that an American National Standards Institute C implementation of the parallel algorithm achieves significant speedup with the increase in the number of processors used. Copyright © 2013 John Wiley & Sons, Ltd.

Selective Determination of Floquet Quantities for the Efficient Assessment of Limit Cycle Stability and Oscillator Noise

We present a mixed time-frequency domain algorithm for the approximate computation of the Floquet quantities (exponents and both direct and adjoint eigenvectors) resulting from the linearization of index-1 differential-algebraic equations around a periodic limit cycle. The approach allows to select the number of Floquet exponents to be calculated approximating the matrix of the obtained eigenvalue problem. The error in the evaluation (for both exponents and eigenvectors) is proved to tend to zero along with the ratio between the norms of the neglected and retained rows of the relevant matrix.

Dynamic Iteration for Coupled Problems of Electric Circuits and Distributed Devices

Coupled systems of differential-algebraic equations (DAEs) may suffer from instabilities during a dynamic iteration. We extend the existing analysis on recursion estimates, error propagation, and stability to (semiexplicit) index-1 DAEs. In this context, we discuss the influence of certain coupling structures and the computational sequence of the subsystems on the rate of convergence. Furthermore, we investigate in detail convergence and divergence for two coupled problems stemming from refined electric circuit simulation. These are the semiconductor-circuit and field-circuit couplings. We quantify the convergence rate and behavior also using Lipschitz constants and suggest an enhanced modeling of the coupling interface in order to improve convergence.

Index-Aware Model Order Reduction for Linear Index-2 DAEs with Constant Coefficients

A model order reduction method for index-2 differential-algebraic equations (DAEs) is introduced, which is based on the intrinsic differential equations and on the remaining algebraic constraints. This extends the method introduced in a previous paper for index-1 DAEs. This procedure is implemented numerically and the results show numerical evidence of its robustness over the traditional methods.

Numerical evaluation of the stability of stationary points of index-2 differential-algebraic equations: Applications to reactive flash and reactive distillation systems

The dynamic behavior of many chemical processes can be represented by an index-2 system of differential-algebraic equations. This index can be reduced by differentiation, but unfortunately the index reduced systems are not guaranteed to possess the same stability characteristics as that of the original system. When the set of differential-algebraic equations can be written in Hessenberg form, the matrix pencil of the linearized system can be used to directly evaluate the stability of a steady state without the need for index reduction. Direct evaluations of stability of reactive flash and reactive distillation are presented. It is also shown that a commonly used index reduction will always result in null eigenvalues at steady state. Stabilization methods were successfully applied to this reduced system. An alternative index reduction method for a reactive flash is generalized and shown to be highly sensitive to minor changes in the jacobian.

Convergence of Linear Multistep Methods and One-Leg Methods for Index-2 Differential-Algebraic Equations with a Variable Delay

AbstractLinear multistep methods and one-leg methods are applied to a class of index-2 nonlinear differential-algebraic equations with a variable delay. The corresponding convergence results are obtained and successfully confirmed by some numerical examples. The results obtained in this work extend the corresponding ones in literature.

Nonlinear MPC and MHE for Mechanical Multi-Body Systems with Application to Fast Tethered Airplanes

Mechanical applications often require a high control frequency to cope with fast dynamics. The control frequency of a nonlinear model predictive controller depends strongly on the symbolic complexity of the equations modeling the system. The symbolic complexity of the model equations for multi-body mechanical systems can often be dramatically reduced by using representations based on non-minimal coordinates, which result in index-3 differential-algebraic equations (DAEs). This paper proposes a general procedure to efficiently treat multi-body mechanical systems in the context of MHE & NMPC using non-minimal coordinate representations, and provides the resulting computational times that can be achieved on a tethered airplane system using code generation.

Network-based Modeling and Index Analysis of Coupled Electro-Mechanical Systems

AbstractWe consider the modeling of multi-physics dynamical systems, in particular the coupling of mechanical and electrical subsystems. The current state of the art in modeling and simulation tools like Dymola or Matlab/Simulink is a network-based modeling via interconnection of several standardized subcomponents. This approach of modeling dynamical systems leads to differential-algebraic equations (DAEs) that can easily be of very high index. In these tools the usual way to deal with high index DAEs is to use computer-algebra packages and symbolic differentiation to identify and resolve the algebraic constraints to obtain a system in minimal coordinates. This approach has several disadvantages. In this contribution we propose a new remodeling approach for coupled electro-mechanical systems. The first step is based on an index reduction formalism for each uni-physics subcomponent by using so-called minimal extension yielding a minimally extended index 1 formulation for each subcomponent. In a second step the index of the overall coupled system is analyzed. We provide conditions for the coupled system to be of index 1.

High-order implicit time integration for unsteady incompressible flows

The spatial discretization of unsteady incompressible Navier–Stokes equations is stated as a system of differential algebraic equations, corresponding to the conservation of momentum equation plus the constraint due to the incompressibility condition. Asymptotic stability of Runge–Kutta and Rosenbrock methods applied to the solution of the resulting index-2 differential algebraic equations system is analyzed. A critical comparison of Rosenbrock, semi-implicit, and fully implicit Runge–Kutta methods is performed in terms of order of convergence and stability. Numerical examples, considering a discontinuous Galerkin formulation with piecewise solenoidal approximation, demonstrate the applicability of the approaches and compare their performance with classical methods for incompressible flows. Copyright © 2011 John Wiley & Sons, Ltd.

Lie group generalized-α time integration of constrained flexible multibody systems

This paper studies a Lie group extension of the generalized-α time integration method for the simulation of flexible multibody systems. The equations of motion are formulated as an index-3 differential-algebraic equation (DAE) on a Lie group, with the advantage that rotation variables can be taken into account without the need of introducing any parameterization. The proposed integrator is designed to solve this equation directly on the Lie group without index reduction. The convergence of the method for DAEs is studied in detail and global second-order accuracy is proven for all solution components, i.e. for nodal translations, rotations and Lagrange multipliers. The convergence properties are confirmed by three benchmarks of rigid and flexible systems with large rotation amplitudes. The Lie group method is compared with a more classical updated Lagrangian method which is also formulated in a Lie group setting. The remarkable simplicity of the new algorithm opens interesting perspectives for real-time applications, model-based control and optimization of multibody systems.