An Evolutionary Field Theorem: Evolutionary Field Optimization in Training of Power-Weighted Multiplicative Neurons for Nitrogen Oxides-Sensitive Electronic Nose Applications.

Neuroevolutionary machine learning is an emerging topic in the evolutionary computation field and enables practical modeling solutions for data-driven engineering applications. Contributions of this study to the neuroevolutionary machine learning area are twofold: firstly, this study presents an evolutionary field theorem of search agents and suggests an algorithm for Evolutionary Field Optimization with Geometric Strategies (EFO-GS) on the basis of the evolutionary field theorem. The proposed EFO-GS algorithm benefits from a field-adapted differential crossover mechanism, a field-aware metamutation process to improve the evolutionary search quality. Secondly, the multiplicative neuron model is modified to develop Power-Weighted Multiplicative (PWM) neural models. The modified PWM neuron model involves the power-weighted multiplicative units similar to dendritic branches of biological neurons, and this neuron model can better represent polynomial nonlinearity and they can operate in the real-valued neuron mode, complex-valued neuron mode, and the mixed-mode. In this study, the EFO-GS algorithm is used for the training of the PWM neuron models to perform an efficient neuroevolutionary computation. Authors implement the proposed PWM neural processing with the EFO-GS in an electronic nose application to accurately estimate Nitrogen Oxides (NOx) pollutant concentrations from low-cost multi-sensor array measurements and demonstrate improvements in estimation performance.

2DOF multi-objective optimal tuning of disturbance reject fractional order PIDA controllers according to improved consensus oriented random search method.

This study presents a Fractional Order Proportional Integral Derivative Acceleration (FOPIDA) controller design methodology to improve set point and disturbance reject control performance. The proposed controller tuning method performs a multi-objective optimal fine-tuning strategy that implements a Consensus Oriented Random Search (CORS) algorithm to evaluate transient simulation results of a set point filter type Two Degree of Freedom (2DOF) FOPIDA control system. Contributions of this study have three folds: Firstly, it addresses tuning problem of FOPIDA controllers for first order time delay systems. Secondly, the study aims fine-tuning of 2DOF FOPIDA control structure for improved set point and disturbance rejection control according to transient simulations of implementation models. This enhances practical performance of theoretical tuning method according to implementation requirements. Thirdly, the paper presents a hybrid controller tuning methodology that increases effectiveness of the CORS algorithm by using stabilizing controller coefficients as an initial configuration. Accordingly, the CORS algorithm performs the fine-tuning of 2DOF FOPIDA controllers to achieve an improved set point and disturbance rejection control performances. This fine-tuning is carried out by considering transient simulation results of 2DOF FOPIDA controller implementation model. Moreover, Reference to Disturbance Ratio (RDR) formulation of the FOPIDA controller is derived and used for measurement of disturbance rejection control performance. Illustrative design examples are presented to demonstrate effectiveness of the proposed method.

Disturbance rejection FOPID controller design in v-domain.

Due to the adverse effects of unpredictable environmental disturbances on real control systems, robustness of control performance becomes a substantial asset for control system design. This study introduces a v-domain optimal design scheme for Fractional Order Proportional-Integral-Derivative (FOPID) controllers with adoption of Genetic Algorithm (GA) optimization. The proposed design scheme performs placement of system pole with minimum angle to the first Riemann sheet in order to obtain improved disturbance rejection control performance. In this manner, optimal placement of the minimum angle system pole is conducted by fulfilling a predefined reference to disturbance rate (RDR) design specification. For a computer-aided solution of this optimal design problem, a multi-objective controller design strategy is presented by adopting GA. Illustrative design examples are demonstrated to evaluate performance of designed FOPID controllers.

Reference-shaping adaptive control by using gradient descent optimizers.

This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC) method for several test scenarios. An experimental study demonstrates application of method for rotor control.

Hurwitz stability analysis of fractional order LTI systems according to principal characteristic equations.

With power mapping (conformal mapping), stability analyses of fractional order linear time invariant (LTI) systems are carried out by consideration of the root locus of expanded degree integer order polynomials in the principal Riemann sheet. However, it is essential to show the left half plane (LHP) stability analysis of fractional order characteristic polynomials in the s plane in order to close the gap emerging in stability analyses of fractional order and integer order systems. In this study, after briefly discussing the relation between the characteristic root orientations and the system stability, the author presents a methodology to establish principal characteristic polynomials to perform the LHP stability analysis of fractional order systems. The principal characteristic polynomials are formed by factorizing principal characteristic roots. Then, the LHP stability analysis of fractional order systems can be carried out by using the root equivalency of fractional order principal characteristic polynomials. Illustrative examples are presented to explain how to find equivalent roots of fractional order principal characteristic polynomials in order to carry out the LHP stability analyses of fractional order nominal and interval systems.

An integer order approximation method based on stability boundary locus for fractional order derivative/integrator operators.

This paper introduces an integer order approximation method for numerical implementation of fractional order derivative/integrator operators in control systems. The proposed method is based on fitting the stability boundary locus (SBL) of fractional order derivative/integrator operators and SBL of integer order transfer functions. SBL defines a boundary in the parametric design plane of controller, which separates stable and unstable regions of a feedback control system and SBL analysis is mainly employed to graphically indicate the choice of controller parameters which result in stable operation of the feedback systems. This study reveals that the SBL curves of fractional order operators can be matched with integer order models in a limited frequency range. SBL fitting method provides straightforward solutions to obtain an integer order model approximation of fractional order operators and systems according to matching points from SBL of fractional order systems in desired frequency ranges. Thus, the proposed method can effectively deal with stability preservation problems of approximate models. Illustrative examples are given to show performance of the proposed method and results are compared with the well-known approximation methods developed for fractional order systems. The integer-order approximate modeling of fractional order PID controllers is also illustrated for control applications.

Probabilistic robust stabilization of fractional order systems with interval uncertainty.

This study investigates effects of fractional order perturbation on the robust stability of linear time invariant systems with interval uncertainty. For this propose, a probabilistic stability analysis method based on characteristic root region accommodation in the first Riemann sheet is developed for interval systems. Stability probability distribution is calculated with respect to value of fractional order. Thus, we can figure out the fractional order interval, which makes the system robust stable. Moreover, the dependence of robust stability on the fractional order perturbation is analyzed by calculating the order sensitivity of characteristic polynomials. This probabilistic approach is also used to develop a robust stabilization algorithm based on parametric perturbation strategy. We present numerical examples demonstrating utilization of stability probability distribution in robust stabilization problems of interval uncertain systems.

Disturbance rejection performance analyses of closed loop control systems by reference to disturbance ratio.

This study investigates disturbance rejection capacity of closed loop control systems by means of reference to disturbance ratio (RDR). The RDR analysis calculates the ratio of reference signal energy to disturbance signal energy at the system output and provides a quantitative evaluation of disturbance rejection performance of control systems on the bases of communication channel limitations. Essentially, RDR provides a straightforward analytical method for the comparison and improvement of implicit disturbance rejection capacity of closed loop control systems. Theoretical analyses demonstrate us that RDR of the negative feedback closed loop control systems are determined by energy spectral density of controller transfer function. In this manner, authors derived design criteria for specifications of disturbance rejection performances of PID and fractional order PID (FOPID) controller structures. RDR spectra are calculated for investigation of frequency dependence of disturbance rejection capacity and spectral RDR analyses are carried out for PID and FOPID controllers. For the validation of theoretical results, simulation examples are presented.

Sonic crystal acoustic switch device.

This study reports a wave-controlled sonic crystal switch device that exhibits a destructive interference-based wave to wave reverse switching effect. By applying control waves, this acoustic device, composed of a two-dimensional square lattice sonic crystal block, reduces acoustic wave transmission from input to output. The finite difference time domain simulation and experimental results confirm the wave-to-wave reverse switching effect at the peak frequencies of the second band. The proposed sonic crystal switch prototype provides a contrast rate of 86% at 11.3 kHz frequency. This wave-to-wave switching effect is useful for controlling wave propagation for smart structure applications.

A distance-based dynamical transition analysis of time series signals and application to biological systems.

This study demonstrates an application of distance-based numerical measures to the phase space of time series signals, in order to obtain a temporal analysis of complex dynamical systems. This method is capable of detecting alterations appearing in the characters of the deterministic dynamical systems and provides a simple tool for the real-time analysis of time series data obtained from a complex dynamical system even with black box functionality. The study presents a possible application of the method in the dynamical transition analysis of real EEG records from epilepsy patients.