New advances in H∞ control and filtering for nonlinear systems

The main objective of this special issue is to summarise recent advances in H∞ control and filtering for nonlinear systems, including time-delay, hybrid and stochastic systems. The published papers provide new ideas and approaches, clearly indicating the advances made in problem statements, methodologies or applications with respect to the existing results. The special issue also includes papers focusing on advanced and non-traditional methods and presenting considerable novelties in theoretical background or experimental setup. Some papers present applications to newly emerging fields, such as network-based control and estimation

A novel maximal-length sequence synchronisation network

Spread Spectrum has become a popular digital modulation scheme in recent years. The advantages the scheme offers, at the expense of bandwidth, make it attractive in a multitude of commercial applications. The most common method, and the one of interest in this thesis, of generating Spread Spectrum is multiplying the data waveform by a wideband, digitally generated waveform. This is referred to as Direct Sequence Spread Spectrum. The characteristics of Spread Spectrum systems are determined by the spreading waveform. A common group of spreading waveforms, and the ones dealt with in this text, are the maximal-length sequences. These are a class of pseudorandom waveforms. Their properties include a two valued autocorrelation function with its maximum value at no code-phase offset. This allows for multiple access to a single resource and the suppression of multi-path interference as adjacent codes have little effect on each other. This same property requires that the receiver must accurately align its replica of the spreading waveform to the transmitted waveform in order to despread the received waveform and demodulate the data. Common methods of synchronisation use a two pronged solution. Firstly the correct code phase is determined. This is referred to as code acquisition. Secondly the clocking frequency of the received waveform must be resolved in order to precisely align the two sequences. This is referred to as code tracking. Receivers therefore tend to be complex and expensive. This thesis involved the investigation of two pseudo-noise synchronisation networks proposed by J .G. van de Groenendaal. These networks offered both code acquisition and tracking in a single robust loop. The investigation, done in co-operation with J..G. van de Groenendaal, persued two avenues. Firstly the loops were simulated. This method allows for the easy alteration of system parameters. Valuable insight into the loop dynamics can thus be gained. Secondly the loops were built on the bench. This allows for the practical confirmation of the results of the simulation. Both synchronisation loops were based on variations of the maximal likelihood phase detector. This phase detector is formed by taking the product of the first derivative with respect to time of the receiver's replica of the transmitted waveform and the received waveform. The initial investigation involved calculating the phase information generated by this phase discriminator for a variety of code-phase and frequency offsets. It was found that there were two stable points in the baseband Spread Spectrum search grid, a grid where a cell consists of a certain code-phase and frequency offset. These stable points existed at no frequency offset, which means that the loops should track the input frequency, and a one or no code-phase offset, which means that the loops should acquire either code-phase. A simple model where the novel synchronisation loop's conditions are represented by a 'ball' resting on the baseband Spread Spectrum search grid as expressed in terms of the integrated phase output of the maximal likelihood phase discriminator was developed. In this model the 'ball' will roll around the surface until one of the two stable points is entered. This describes quite accurately the paths the novel synchronisation loop does in fact take through the baseband Spread Spectrum search grid. The first loop is based directly on the maximal likelihood phase detector. The differentiator is thus in the feedback path of the loop. This results in the loop being unstable and parameter sensitive. Moving the differentiator into the input path, as in the second loop, resulted in a more stable loop. This loop therefore offered a complete, simple synchronisation solution. The novel synchronisation loop with the differentiator in the input path was found to operate at signal-to- noise ratios of -2 dB. Improvement of this signal-to-noise ratio does not offer any advantages in a Spread Spectrum environment as the loop needs to work in a coherent system where the radio frequency carrier must be resolved before the receiver's pseudo-noise sequence can be synchronised. A radio frequency carrier cannot be easily resolved at signal-to-noise ratios lower than O dB. The loop was further adapted to operate in the data environment. Under conditions of data modulation the received waveform is randomly inverted by the data. This results in the loop being driven out of lock. The phase discriminator's slope, having locked on a certain polarity, cannot track an input of the opposite polarity. The loop was adapted by including detection circuitry that would monitor the state of the receiver with respect to the incoming data waveform and alter the polarity of the of the discriminator's slope where necessary. During the prototyping of the loop on the bench certain implementations were investigated. These included the signed edge detector, a wideband low noise implementation of a square wave differentiator, and the synchronous oscillator, a form of injection locked oscillator. The loop was shown to achieve synchronisation. The novel synchronisation loop with the differentiator in the input path is thus capable of synchronising two maximal-length sequences in both code-phase and frequency

On Convergence of Tracking Differentiator with Multiple Stochastic Disturbances

In this paper, the convergence and noise-tolerant performance of a tracking differentiator in the presence of multiple stochastic disturbances are investigated for the first time. We consider a quite general case where the input signal is corrupted by additive colored noise, and the tracking differentiator itself is disturbed by additive colored noise and white noise. It is shown that the tracking differentiator tracks the input signal and its generalized derivatives in mean square and even in almost sure sense when the stochastic noise affecting the input signal is vanishing. Some numerical simulations are performed to validate the theoretical results

Robust Tracking of Bio-Inspired References for a Biped Robot Using Geometric Algebra and Sliding Mode Control

Controlling walking biped robots is a challenging problem due to its complex and uncertain dynamics. In order to tackle this, we propose a sliding mode controller based on a dynamic model which was obtained using the conformal geometric algebra approach (CGA). The CGA framework permits us to use lines, points, and other geometric entities, to obtain the Lagrange equations of the system. The references for the joints of the robot were bio-inspired in the kinematics of a walking human body. The first and second derivatives of the reference signal were obtained through an exact robust differentiator based on high order sliding mode. The performance of the proposed control schemes are illustrated through simulation.ITESO, A.C

Theory of nonlinear feedback under uncertainty

AbstractOur main purpose here is to demonstrate the potential of a new approach which is an important expansion of the feedback concept: we have chosen what seemed a natural way of tackling some traditional problems of the control theory and of comparing the results against those offered by conventional methods.The main problem considered is the output stabilization for uncertain plants. Using structural transformations, uncertain systems can change to the form convenient for output feedback design. Synthesis of observer-based control for asymptotical stabilization or uniform ultimate boundedness of the closed-loop system is provided.We consider the notions of asymptotic and exponential invariance of a control system implies its suboptimality.A method is described for stabilization of uncertain discrete-time plants of which only compact sets are known to which plants parameters and exogenous signals belong. New approaches for solving some central problems of mathematical control theory are considered for nonlinear dynamical systems. New criterious of local and global controllability and stabilizability are indicated and some synthesis procedures are suggested

Recent Advances in Robust Control

Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics

Design and analysis of genetic feedback architectures for synthetic biology

Synthetic Biology seeks to design and assemble novel biological systems with favourable properties. It allows us to comprehend and modify the fundamental mechanisms of life and holds significant promise in revolutionizing current technologies ranging from medicine and biomanufacturing to energy and environmental protection. Biological processes constitute remarkably complex dynamical systems operating impeccably well in messy and constantly changing environments. Their ability to do so is rooted in sophisticated molecular control architectures crafted by natural evolutionary innovation over billions of years. Such control architectures, often blended with human-engineering approaches, are the key to realizing efficient and reliable synthetic biological systems. Aiming to accelerate the development of the latter, the present thesis addresses some fundamental challenges in biomolecular systems and control design. We begin by elucidating biological mechanisms of temporal gradient computation, enabling cells to adjust their behaviour in response to anticipated environmental changes. Specifically, we introduce biomolecular motifs capable of functioning as highly tunable and accurate signal differentiators to input molecular signals around their nominal operation. We investigate strategies to deal with high-frequency input signal components which can be detrimental to the performance of most differentiators. We ascertain the occurrence of such motifs in natural regulatory networks and demonstrate the potential of synthetic experimental realizations. Our motifs can serve as reliable speed biosensors and can form the basis for derivative feedback control. Motivated by the pervasiveness of Proportional-Integral-Derivative (PID) controllers in modern technological applications, we present the realization of a PID controller via biomolecular reactions employing, among others, our differentiator motifs. This biomolecular architecture represents a PID control law with set point weighting and filtered derivative action, offering robust regulation of a single-output biological process with enhanced dynamic performance and low levels of stochastic noise. It is characterized by significant ease of tuning and can be of particular experimental interest in molecular programming applications. Finally, we investigate efficient regulation strategies for multi-output biological processes with internal coupling interactions, expanding previously established single-output control approaches. More specifically, we propose control schemes allowing for robust manipulation of the outputs in various ways, namely manipulation of their product/ratio, linear combinations of them as well as manipulation of each of the outputs independently. Our analysis is centered around two-output biological processes, yet the scalability of the proposed regulation strategies to processes with a higher number of outputs is highlighted. In parallel, their experimental implementability is explored in both in vivo and in vitro settings