P.P.J. van den Bosch

A Solution of the Unit Commitment Problem Via Decomposition and Dynamic Programming

Each day power generating units have to be selected to realize a reliable production of electric energy with the fewest fuel costs. This paper proposes decomposition and dynamic programming as techniques for solving the unit commitment problem, a high- dimensional non-linear, mixed-integer optimization problem. Experiments indicate that the proposed methods locate in less time a better solution than many existing techniques.

Optimal Dynamic Dispatch Owing to Spinning-Reserve and Power-Rate Limits

This paper deals with the formulation and solution of the optimal dynamic dispatch problem owing to spinning-reserve and power-rate limits. The power production of a thermal unit is considered as a dynamic system, which limits the maximum increase and decrease of power. The solution is obtained with a special projection method having conjugate search directions that quickly and accurately solves the associated non-linear programming problem with up to 2400 variables and up to 9600 constraints.

Modelling of periodically switching networks

Two time-domain analysis methods for periodically switched systems, like converters, are presented. The first method analyzes the steady-state periodic behavior of the system, while the second describes the transient behavior. In contrast with state-space averaging, the methods do not use approximations, so exact results are obtained. The methods give more insight into the dynamical behavior of the system. This knowledge is useful in designing controllers.<<ETX>>

Scheduling of power generation via large-scale nonlinear optimization

We investigate methods for solving high-dimensional nonlinear optimization problems which typically occur in the daily scheduling of electricity production: problems with a nonlinear, separable cost function, lower and upper bounds on the variables, and an equality constraint to satisfy the demand. If the cost function is quadratic, we use a modified Lagrange multiplier technique. For a nonquadratic cost function (a penalty function combining the original cost function and certain fuel constraints, so that it is generally not separable), we compare the performance of the gradient-projection method and the reduced-gradient method, both with conjugate search directions within facets of the feasible set. Numerical examples at the end of the paper demonstrate the effectiveness of the gradient-projection method to solve problems with hundreds of variables by exploitation of the special structure.

A robust disturbance-based control and its application

A simple and robust disturbance-based control (DBC) method is introduced in this paper which employs a nominal model as the disturbance observer to estimate the overall disturbance, which includes the model-plant mismatch error, unmeasured external disturbances and cross-coupling in multivariable systems. The feedback of the estimated disturbance can eliminate the effect of external disturbances and structured perturbation caused by parameter variation, and decouple a multi-input multi-output (MIMO) system into a number of single-input single output (SISO) nominal subsystems. The root-locus method can be used to analyse the stability of DBC controlled systems and derive the design criterion. Subsequently, a robust controller can be designed based on each SISO nominal system. DBC can help the application of the H ∞ theory and the achievement of diagonal dominance. Application of DBC on a Bosch SCARA-type robot is presented to achieve decentralized joint control. Simulation results confirm the viability of ...

Case studies in event-driven control

The majority of research in control engineering considers periodic or time-triggered control systems with equidistant sample intervals. However, practical cases abound in which it is of interest to consider event-driven control systems, where the sampling is event-triggered. Although there are various benefits of using event-driven control like reducing resource usage (e.g. processor and communication load), their application in practice is hampered by the lack of a system theory for event-driven control systems. In this paper we present two types of event-driven controllers and show their potential via industrially relevant case studies and indicate initial theoretical results.

Optimal Static Dispatch With Linear, Quadratic and Non-Linear Functions of the Fuel Costs

This paper describes and compares several fast algorithms for the solution of the static dispatch problem for thermal power units without transmission losses. Both linear, quadratic and non-linear functions are discussed to describe the fuel costs. Moreover, units that use two fuels at the same time and units with fuel constraints are discussed.

On the unification of predictive control algorithms

The design of the unified predictive controller (UPC) is presented. It is shown that the UPC control law is equivalent to a control law which generates the controller output by means of a linear combination of past process outputs, controller outputs and the reference trajectory. After defining a unified process model which can be used for a number of well-known process models, the authors derive its minimum-variance (MV) i-step-ahead predictor. It is shown that this predictor can be rewritten in a form consisting of two parts of which one does not depend on the noise model and the other does. This form of the unified MV i-step-ahead predictor shows that deviations between process and model, caused by model mismatch or disturbances, are filtered before they are added to the predictions.<<ETX>>

Adaptive attitude control for large-angle Slew manoeuvres

Abstract An attitude control system of a satellite that enables a fast reorientation of the satellite by means of one single three-axes slew about the Euler axis is described. It is made adaptive in order to be able to deal with the many nonlinearities associated with large angle slews of rigid-body satellites controlled by means of reaction wheels. Then a smooth slew about the Euler axis can be made. An improvement in this model reference adaptive controller is obtained by introducing the model updating concept. Simulation results with the IRAS satellite are given.

State space identification of closed loop systems

Within the joint input/output identification scheme, stochastic realization is used to solve the spectral factorization problem, thus providing a time-domain closed-loop identification method. First, a stochastic realization of the joint closed-loop system is obtained. Through state space partitioning, nonminimal realizations of the subprocesses can be calculated. Balancing reduction then provides minimal realizations of the subprocesses in the loop. Simulation examples show good results with the proposed method.<<ETX>>