Conversion of descriptor representations to state-space form: an extension of the shuffle algorithm

This paper proposes a systematic procedure for the determination of state-space models from an available descriptor representation of a linear dynamic system. The goal is to determine a state equation, a set of algebraic equations and an output equation in terms of the state and input variables. It is shown that standard methods may fail to convert the descriptor representation to state-space form, even for simple electrical circuit models obtained from Kirchoff’s laws and constitutive element equations. A novel procedure to address this problem is then proposed as an extension of the classic shuffle algorithm combined with a singular value decomposition approach. In addition to an illustrative example involving a simple electrical circuit, the proposed method is employed in a case study involving the modeling of three-dimensional RLC networks with a large number of components

Constrained pre-equalization accounting for multi-path fading emulated using large RC networks: applications to wireless and photonics communications

Multi-path propagation is modelled assuming a multi-layer RC network with randomly allocated resistors and capacitors to represent the transmission medium. Due to frequency-selective attenuation, the waveforms associated with each propagation path incur path-dependent distortion. A pre-equalization procedure that takes into account the capabilities of the transmission source as well as the transmission properties of the medium is developed. The problem is cast within a Mixed Integer Linear Programming optimization framework that uses the developed nominal RC network model, with the excitation waveform customized to optimize signal fidelity from the transmitter to the receiver. The objective is to match a Gaussian pulse input accounting for frequency regions where there would be pronounced fading. Simulations are carried out with different network realizations in order to evaluate the sensitivity of the solution with respect to changes in the transmission medium mimicking the multi-path propagation. The proposed approach is of relevance where equalization techniques are difficult to implement. Applications are discussed within the context of emergent communication modalities across the EM spectrum such as light percolation as well as emergent indoor communications assuming various modulation protocols or UWB schemes as well as within the context of space division multiplexing

Measurement and control of emergent phenomena emulated by resistive-capacitive networks, using fractionalorder internal model control and external adaptive control

A fractional-order internal model control technique is applied to a three-dimensional resistive-capacitive network to enforce desired closed loop dynamics of first order. In order to handle model mismatch issues resulting from the random allocation of the components within the network, the control law is augmented with a model-reference adaptive strategy in an external loop. By imposing a control law on the system to obey first order dynamics, a calibrated transient response is ensured. The methodology enables feedback control of complex systems with emergent responses and is robust in the presence of measurement noise or under conditions of poor model identification. Furthermore, it is also applicable to systems that exhibit higher order fractional dynamics. Examples of feedback-controlled transduction include cantilever positioning in atomic force microscopy or the control of complex de-excitation lifetimes encountered in many types of spectroscopies, e.g., nuclear magnetic, electron-spin, microwave, multiphoton fluorescence, Förster resonance, etc. The proposed solution should also find important applications in more complex electronic, microwave, and photonic lock-in problems. Finally, there are further applications across the broader measurement science and instrumentation community when designing complex feedback systems at the system level, e.g., ensuring the adaptive control of distributed physiological processes through the use of biomedical implants