Hybrid GA–BF based intelligent PID controller tuning for AVR system

This paper deals with hybrid system (GA–BF) based on the conventional GA (Genetic Algorithm) and BF (Bacterial Foraging) which is the social foraging behavior of bacteria. A variety of test function is introduced and simulated to illustrate the characteristics and performance by mutation, crossover, variation of step size, variation of chemotactic step, and variation of lifetime of bacteria in the proposed hybrid system GA–BF. The simulated results represent that the proposed method is highly satisfactory. This approach provides us with novel hybrid model based on foraging behavior and also with a possible new connection between evolutionary forces in social foraging and distributed nongradient optimization algorithm design for global optimization over noisy surfaces.     

Congestion management by determining optimal location of series FACTS devices using hybrid bacterial foraging and Nelder–Mead algorithm

In this paper, the Thyristor-Controlled Series-Compensated (TCSC) devices are located for congestion management in the power system by considering the non-smooth fuel cost function and penalty cost of emission. For this purpose, it is considered that the objective function of the proposed optimal power flow (OPF) problem is minimizing fuel and emission penalty cost of generators. A hybrid method that is the combination of the bacterial foraging (BF) algorithm with Nelder–Mead (NM) method (BF-NM) is employed to solve the OPF problems. The optimal location of the TCSC devices are then determined for congestion management. The size of the TCSC is obtained by using of the BF-NM algorithm to minimize the cost of generation, cost of emission, and cost of TCSC. The simulation results on IEEE 30-bus, modified IEEE 30-bus and IEEE 118-bus test system confirm the efficiency of the proposed method for finding the optimal location of the TCSC with non-smooth non-convex cost function and emission for congestion management in the power system. In addition, the results clearly show that a better solution can be achieved by using the proposed OPF problem in comparison with other intelligence methods.     

Tuning of a decoupling controller for a 2×2 system using iterative feedback tuning

Iterative feedback tuning is used to tune a decoupling controller for a 2×2 multivariable system. The tuning is carried out in two steps. In the first step the coefficients of two proportional decoupling controllers are tuned, and in the second step two PD-controllers are tuned. The approach is evaluated on a nonlinear simulation model of a two-link manipulator. The evaluation is carried out using two different reference trajectories and also in the presence of friction. The resulting closed loop systems show satisfactory behavior in all three cases.     

Clustering MIT–BIH arrhythmias with Ant Colony Optimization using time domain and PCA compressed wavelet coefficients

In this paper, Ant Colony Optimization (ACO) based clustering analysis of ECG arrhythmias taken from the MIT–BIH Arrhythmia Database is proposed. Both time domain and discrete wavelet transform (DWT) based frequency domain features are used in the analysis. Since the number of wavelet coefficients are huge amount as compared to the time domain parameters, Principal Component Analysis (PCA) based compression is applied on them in order to decrease their number to the number of time domain features. Then, the reduced numbers of frequency parameters are combined with the time domain features, in order to get the total feature sets. Different types of feature sets are tried and the classification results are compared. These are: time domain feature set, frequency domain feature set and the mixture of them. A neural network algorithm is developed in parallel to verify and measure the ACO classifier's success. Moreover, linear discriminant analysis (LDA) is used to show the effect of clustering on the system's results. The method is tested with MIT–BIH database to classify normal beats and five different critical and having vital importance arrhythmia types. Chosen six classes are normal sinus rhythm, premature ventricular contraction (PVC), atrial premature contraction (APC), right bundle branch block (RBBB), ventricular fusion (F) and fusion (f). Comparison results indicate that the mixture feature set gave a better success for the classification.     

Finding optimal strategies in a multi-period multi-leader–follower Stackelberg game using an evolutionary algorithm

Stackelberg games are a classic example of bilevel optimization problems, which are often encountered in game theory and economics. These are complex problems with a hierarchical structure, where one optimization task is nested within the other. Despite a number of studies on handling bilevel optimization problems, these problems still remain a challenging territory, and existing methodologies are able to handle only simple problems with few variables under assumptions of continuity and differentiability. In this paper, we consider a special case of a multi-period multi-leader–follower Stackelberg competition model with non-linear cost and demand functions and discrete production variables. The model has potential applications, for instance in aircraft manufacturing industry, which is an oligopoly where a few giant firms enjoy a tremendous commitment power over the other smaller players. We solve cases with different number of leaders and followers, and show how the entrance or exit of a player affects the profits of the other players. In the presence of various model complexities, we use a computationally intensive nested evolutionary strategy to find an optimal solution for the model. The strategy is evaluated on a test-suite of bilevel problems, and it has been shown that the method is successful in handling difficult bilevel problems.     

Design of reduced search space strategy based on integration of Nelder–Mead method and pattern search algorithm with application to economic load dispatch problem

This paper presents a novel hybrid technique for the solution of economic load dispatch problem with valve point loading effect using Nelder–Mead (NM) simplex method and pattern search (PS) algorithm. Strength of globalized NM optimization algorithm has been employed to explore the search space for near optimal solution, and PS algorithm is used in combination with a search space reduction strategy, incorporating the principles of selection and stochastic reproduction, to fine-tune the result. The proposed technique has been applied to three different systems having 3, 13 and 40 generating units to demonstrate the application for small to large load dispatch set-up. The efficacy of the design scheme is established from comparison of the results with the state-of-the-art solvers, and it is found that the proposed scheme gives the best result in terms of mean cost while the average computational time is less than most of the reported methods.

     

A computational method for optimal control problems with a free final time using the modified quasilinearization and the gradient method†

This paper presents a computational method for the solution of a class of optimal control problems with a free final time. The method is based on the combination of the modified quasilinearization and the gradient method. A numerical example is included for illustration.     

A client–server architecture for remotely controlling a robot using a closed-loop system with a biological neuroprocessor

This paper introduces an open-source real-time system that remotely controls a robot using human neuroblastoma cultures and a client–server architecture. Multielectrode array set-ups have been designed for direct culturing of neural cells over silicon or glass substrates, providing the capability simultaneously to stimulate and record populations of neural cells. However, it is very difficult to attach these neural cells to the robot structure due to the special conditions of the biological material. The main objective of this research is to build a client–server system for remotely connecting a robot to a neural culture in a closed-loop experimentation. The robot sensors will feed the biological neuroprocessor, while the neural activity will be used for guiding the robot, controlling in this way the robotic behaviour.     

Modification of a two-dimensional fast Fourier transform algorithm with an analog of the Cooley–Tukey algorithm for image processing

Two-dimensional fast Fourier transform (FFT) for image processing and filtering is widely used in modern digital image processing systems. This paper concerns the possibility of using a modification of two-dimensional FFT with an analog of the Cooley–Tukey algorithm, which requires a smaller number of complex addition and multiplication operations than the standard method of calculation by rows and columns.     

A parameter uniform numerical method for a system of singularly perturbed convection–diffusion equations with discontinuous convection coefficients

In this paper, a weakly coupled system of two singularly perturbed convection-diffusion equations with discontinuous convection coefficients is examined. A finite difference scheme on Shishkin mesh generating the parameter uniform convergence in the global maximum norm is constructed for solving this problem. Numerical results which are in agreement with the theoretical results are presented.     

An improved stability result for linear time-delay system using a new Lyapunov–Krasovskii functional and extended reciprocally convex inequality

This paper is concerned with the stability analysis of a linear system with interval time-varying delay using an augmented Lyapunov–Krasovskii (LK) functional approach. A delay-dependent stability criterion is developed in LMI framework to estimate the maximum allowable bound of the time-delay within which the system remains asymptotically stable in the sense of Lyapunov. Conservatism in the proposed delay-dependent stability analysis is reduced by introducing a new LK functional along with the Wirtinger's inequality and extended reciprocally convex matrix inequality. Finally, two numerical examples and the load frequency control problem have been solved to validate the superiority of the proposed stability criterion compared to existing literature.     

Application of fixed point-collocation method for solving an optimal control problem of a parabolic–hyperbolic free boundary problem modeling the growth of tumor with drug application

In this paper, employing a fixed point-collocation method, we solve an optimal control problem for a model of tumor growth with drug application. This model is a free boundary problem and consists of five time-dependent partial differential equations including three different first-order hyperbolic equations describing the evolution of cells and two second-order parabolic equations describing the diffusion of nutrient and drug concentration. In the mentioned optimal control problem, the concentration of nutrient and drug is controlled using some control variables in order to destroy the tumor cells. In this study, applying the fixed point method, we construct a sequence converging to the solution of the optimal control problem. In each step of the fixed point iteration, the problem changes to a linear one and the parabolic equations are solved using the collocation method. The stability of the method is also proved. Some examples are considered to illustrate the efficiency of method.     

A new multi-mode multi-input–multi-output (MIMO) converter in an efficient low-voltage energy harvesting system for a gas sensor

Microsystem Technologies - This paper presents a new multi-mode multi-input–multi-output (MIMO) converter with a battery for operating an energy harvesting (EH) system for gas sensors. In...     

A parameter-uniform second order numerical method for a weakly coupled system of singularly perturbed convection–diffusion equations with discontinuous convection coefficients and source terms

In this article, a parameter-uniform hybrid numerical method is presented to solve a weakly coupled system of two singularly perturbed convection–diffusion equations with discontinuous convection coefficients and source terms. Due to these discontinuities, interior layers appear in the solution of the problem considered. The hybrid numerical method uses the standard finite difference scheme in the coarse mesh region and the cubic spline difference scheme in the fine mesh region which is constructed on piecewise-uniform Shishkin mesh. Second order one sided difference approximations are used at the point of discontinuity. Error analysis is carried out and the method ensures that the parameter-uniform convergence of almost the second order. Numerical results are provided to validate the theoretical results.     

Erratum to “A stochastic controller for a scalar linear system with additive Cauchy noise” [Automatica 50(1) (2014) 114–127]

A stochastic control scheme is developed for scalar, discrete-time, and linear-dynamic systems driven by Cauchy distributed process and measurement noises. When addressing the optimal control problem for such systems, the standard quadratic cost criteria cannot be used. In this study we introduce a new objective function that is functionally similar to the Cauchy probability density function. The performance index, defined as the expectation of this objective function with respect to the Cauchy densities, exists. The dynamic programming solution to the fixed and finite horizon optimal control problem that uses this performance index appears to be intractable. Therefore, a moving horizon optimal model predictive control problem is implemented, for which the conditional expected value of the objective function and its gradients can be computed in closed   form and without assumptions such as certainty equivalence. Numerical results are shown for this m$m$-step model predictive optimal controller and compared to a similar, Linear–Exponential–Gaussian model predictive controller. An essential difference between the Cauchy and Gaussian controllers when applied to a system with Cauchy noises is that, while the Gaussian controller is linear and reacts strongly to all noise pulses, the Cauchy controller can differentiate between measurement and process noise pulses by ignoring the former while responding to the latter. This property of the Cauchy controller occurs when an impulsive measurement noise is more likely than an impulsive process noise. The Cauchy and Gaussian controllers react similarly when applied to a system with Gaussian noises, demonstrating the robustness of the proposed control scheme.