Rogelio Luck

An observer-based compensator for distributed delays

This paper presents an algorithm for compensating delays that are distributed between the sensor(s), controller and actuator(s) within a control loop. This observer-based algorithm is specially suited to compensation of network-induced delays in integrated communication and control systems. The robustness of the algorithm relative to plant model uncertainties has been examined.

Experimental verification of a delay compensation algorithm for integrated communication and control systems

Advances in the technology of complex control systems demand high-speed and reliable communications between the individual components and subsystems for decision making and control. This can be accomplished by integrated communication and control systems which use asynchronous time-division-multiplexed networks. Unfortunately, these networks introduce randomly varying distributed delays as a result of time-division multiplexing. A predictor-controller algorithm has been developed with the objective of mitigating the detrimental effects of the network-induced delays that are distributed between the sensor(s), controller and actuator(s) within a control loop. This paper presents the implementation and verification of the above delay compensation algorithm. Performance of the delay compensator has been experimentally verified on an IEEE 802.4 network testbed for velocity control of a d.c. servomotor.

An introduction to sensor signal validation in redundant measurement systems

Some of the key concepts of sensor redundancy management are discussed and illustrated by simple examples. The focus is on redundancy management in fault detection and isolation with the emphasis on the parity space. A model of a multiply redundant measurement system is presented. The generation of residuals is considered, and the concept of parity space is explained. Failure detection, including sequential testing, is then addressed.<<ETX>>

Solution to inverse heat conduction problems employing singular value decomposition and model-reduction

Abstract A new and simple method for solving linear, inverse heat conduction problems using temperature data containing significant noise is presented in this paper. The method consists in a straightforward application of singular-value decomposition to the matrix form of Duhamels principle. A physical interpretation of the method is given by discussing the frequency-domain interpretation of the decomposition. Basically, rows and columns are removed from the decomposed matrices that are associated with small singular values that are shown to be associated with frequencies where the signal-to-noise ratio is small. The technique is demonstrated by considering a standard one-dimensional example. Advantages of the new method are reduction in matrix size, robust treatment of noisy temperature data, optimal in the least-squares sense, and lack of ad hoc parameters.

Comparisons and improvements concerning the accuracy and robustness of inverse heat conduction algorithms

This article describes a detailed investigation concerning the accuracy and robustness of several algorithms for solving the inverse heat conduction problem (IHCP). A variety of existing methods are classified into three categories: the direct inverse solutions, the observer-based solutions, and the optimization type solutions. The typical methods in each category are briefly analyzed and reviewed, i.e., whole domain regularization, optimal solution, and singular value decomposition (SVD) in the direct inverse category; sequential estimation in the observer-based category; and conjugate gradient functional optimization in the optimization category. An algorithm calibration procedure is used to ensure the best performance with each method. A detailed uncertainty analysis including systematic uncertainties and auto-correlations is described and used to calculate the uncertainty due to system parameters and temperature measurements. Accuracy and robustness indices are suggested to evaluate the performance of each method considered. Finally, a zero-phase, low-pass filter post-processing technique is proposed to improve the robustness in performance of the methods with weak accuracy or robustness. Several simulation results show comparisons of the concerned algorithm in terms of accuracy and robustness, and the effect of the proposed post-processing technique.

Explicit Solutions for Transcendental Equations

A simple method to formulate an explicit expression for the roots of any analytic transcendental function is presented. The method is based on Cauchys integral theorem and uses only basic concepts of complex integration. One convenient method for numerically evaluating the exact expression is presented. The application of both the formulation and evaluation of the exact expression is illustrated for several classical root finding problems.

Supervisory Feed-Forward Control for Real-Time Topping Cycle CHP Operation

This paper presents an energy dispatch algorithm for real-time topping cycle cooling, heating, and power (CHP) operation for buildings with the objective of minimizing the operational cost, primary energy consumption (PEC), or carbon dioxide emission (CDE). The algorithm features a supervisory feed-forward control for real-time CHP operation using short-term weather forecasting. The advantages of the proposed control scheme for CHP operation are (a) relatively simple and efficient implementation allowing realistic real-time operation, (b) optimized CHP operation with respect to operational cost, PEC, or CDE, and (c) increased site-energy consumption resulting in less dependence on the electric grid. In the feed-forward portion of the control scheme, short-term electric, cooling, and heating loads are predicted using the U.S. Department of Energy benchmark small office building model. The results are encouraging regarding the potential saving of operational cost, PEC, and CDE from using the control system for a CHP system with electric and thermal energy storages.

Observability under recurrent loss of data

An account is given of the concept of extended observability in finite-dimensional linear time-invariant systems under recurrent loss of data, where the state vector has to be reconstructed from an ensemble of sensor data at nonconsecutive samples. An at once necessary and sufficient condition for extended observability that can be expressed via a recursive relation is presented, together with such conditions for this as may be related to the characteristic polynomial of the state transition matrix in a discrete-time setting, or of the system matrix in a continuous-time setting.

On the design of piezoelectric sensors and actuators

Abstract Piezoelectric devices are becoming more common with the introduction of smart sensors and actuators, and new developments in piezoelectric polymers and ceramics. However, as the authors found, obtaining relevant information for a comprehensive design of piezoelectric sensors and actuators is quite an ordeal. The literature on piezoelectricity is mainly divided on oversimplified explanations based on quartz crystals or on journals and books requiring an extensive background in solid state physics. This paper provides a non-trivial description of piezoelectricity from the perspective of sensor/actuator design. Contributions include: (a) using a simple matrix approach to (i) clearly describe the piezoelectric relationships, and (ii) clearly show how to manipulate the boundary conditions to experimentally obtain the constitutive parameters; (b) showing how the coefficients in the transfer function of a pressure sensor vary as the mode of operation change from isothermal to adiabatic by defining effective capacitances, permitivity, piezoelectric, and compliance constants; (c) showing that the wave equation is a natural result of introducing a kinetic energy term into the energy balance.

Analytic Solutions for Optimal Power Generation Unit Operation in Combined Heating and Power Systems

This paper presents an analytic approach for defining optimal operation decisions for a power generation unit (PGU) in combined heating and power (CHP) systems. The system is optimized with respect to cost, and the independent variables are the thermal load and the electric load. Linear programming is a common tool used to find the optimal PGU operation for a given combination of thermal and electric loads, but these methods are more computationally intensive than the analytical approach proposed in this paper. The analytic process introduced in this paper shows that the optimal PGU operation for all possible thermal and electric loads can be decided by simple and explicit equations even when the efficiency of the PGU is allowed to vary with PGU loading. Moreover, the analysis reveals that for all possible load conditions, the optimal CHP system operation is based on either following the electric load (FEL) or following the thermal load (FTL) strategies. The cost ratio, i.e., the ratio of the electricity price to the fuel price, is introduced as the key parameter used for making optimal decisions. Cost ratios in Chicago, IL and Philadelphia, PA are used as case studies to show the effect that different cost ratios have on the optimal operation decisions for each possible input load.