Observer-based tracking control for single machine infinite bus system via flatness theory

In this research, we aim to use the flatness control theory to develop a useful control scheme for a single machine connected to an infinite bus (SMIB) system taking into account input magnitude and rate saturation constraints. We adopt a fourth-order nonlinear SMIB model along an exciter and a turbine governor as actuators. According to the flatness-based control strategy, first we show that the adopted nominal SMIB model is a flat system. Then, we develop a full linearizing state feedback as well as an outer integral-type loop to ensure suitable tracking performances for the power and voltage as well as the angular velocity outputs. We assume that only the angular velocity of the generator is available to be measured. So, we provide a linear Luenberger observer to estimate the remaining states of the system. Also, the saturation nonlinearities are transferred to the linear part of the system and they are canceled out using their estimations. The efficiency and usefulness of the proposed observer-controller against faults are illustrated using simulation tests in Eurostag and Matlab. The results show that the clearing critical time of the introduced methodology is larger than the classical control approaches and the proposed observer-based flatness controller exhibits over much less control energy compared to the classic IEEE controllers

Friend recommendation based on the Luscher color theory: Twitter use case

At the area of information technology, social networks are becoming an unavoidable part of the Internet usage, due to their facilities for users as well as the benefits to the providers. However, the popularity and thereby, the success of social networks depends highly on number of the network members. This in turn, depends on considerations for several criteria such as networking and number of networks. On the other hand, it is believed that suggestion of appropriate friends to members performed by an effective recommender system can lead to suitable content ranking and consequently, impact the growth of the network in significant sense. The current paper introduces a novel method of recommending celebrities in a social network based on genetic algorithm and the concept of color psychology. The proposed method is applied to Twitter social network as case study, through which the cost function of the user is first optimized to achieve the ideal weights, and the celebrities are then ranked based on the specified parameters as follower and following counts, background color and description. The system is tested using real data of celebrities and number of 100 users with identical parameters. The results evidence the closest recommendation in terms of affordable recommendation error rates as low as 7.6% based on the psychological data validation

Adaptive control realization for canonic Caputo fractional-order systems with actuator nonlinearity: application to mechatronic devices

Nonlinearities, such as dead-zone, backlash, hysteresis, and saturation, are common in the mechanical and mechatronic systems’ components and actuators. Hence, an effective control strategy should take into account such nonlinearities which, if unaccounted for, may cause serious response problems and might even result in system failure. Input saturation is one of the most common nonlinearities in practical control systems. So, this article introduces a novel adaptive variable structure control strategy for nonlinear Caputo fractional-order systems despite the saturating inputs. Owing to the complex nature of the fractional-order systems and lack of proper identification strategies for such systems, this research focuses on the canonic systems with complete unknown dynamics and even those with model uncertainties and external noise. Using mathematical stability theory and adaptive control strategy, a simple stable integral sliding mode control is proposed. The controller will be shown to be effective against actuator saturation as well as unknown characteristics and system uncertainties. Finally, two case studies, including a mechatronic device, are considered to illustrate the effectiveness and practicality of the proposed controller in the applications

Practical finite time vibration suppression of mechatronic systems using proportional–integral–derivative variable structure controls with dead-band nonlinearity

Vibration is an intrinsic phenomenon in many mechanical and mechatronic applied devices and undesirable vibration can either degrade the performance of the system or lead to unpredictable outputs. The main purpose of this article is to introduce a novel second-order proportional–integral–derivative sliding mode control methodology to suppress the undesirable vibrations of a class of applied dynamical systems with applications to mechatronic and mechanical devices. After designing a nonlinear proportional–integral–derivative terminal sliding manifold, rigorous mathematics are provided to guarantee that the origin is a practical finite time stable equilibrium point. Consequently, two efficient control laws are proposed to ensure the occurrence of the sliding motion with and/or without system unknown parameters. Motivated by situations encountered in practice, unknown lumped uncertainties are also added to the system and their impacts are tackled using adaptive control techniques. Furthermore, a hard nonlinear dead-band function is utilized in the control input and its effects such as lags and delays appeared on the control signals as well as on the system outputs are dealt with by the proposed proportional–integral–derivative variable structure controller. The proposed second-order variable structure controller not only utilizes the simple effective design approach of the proportional–integral–derivative controllers to ensure a reasonable transient performance, but also displays fast convergence properties demonstrated in non-singular terminal sliding modes. Finally, through simulation studies, it is confirmed that the proposed control strategy is effective in vibration attenuation of microelectromechanical resonators

Finite Time Sliding Mode Control of Connected Vehicle Platoons Guaranteeing String Stability

We consider the control design problem for a connected vehicle platoon. It is known that the platooning of vehicles in highways brings several advantages such as reduction of air pollution, increase of safety and facilitating the traffic flow. So, in this paper, a fast control algorithm is proposed to enhance the stability convergence rate of smart platoons. Subsequently, a robust terminal sliding mode controller is derived so that to not only guarantee the finite time fast stability of the connected vehicles, but also to ensure that the global string stability of the platoon is achieved via defining a new spacing error variable. The proposed sliding mode controller gets benefits of a non-singular switching sliding manifold to result in an exact finite time sliding motion dynamics. Considering the effects of uncertainties in the vehicle model as well as time varying external perturbations (such as the effects of wind, snow, etc) affecting the vehicle dynamics, a second-order nonlinear model is adopted for the vehicles and the robustness of the proposed control algorithm is theoretically proved using Lyapunov theory. At last, computer simulations illustrate the effective and fast performance of the introduced platooning strategy

Application of Dynamic Mutated Particle Swarm Optimization Algorithm to Design Water Distribution Networks

This paper proposes the application of a new version of the heuristic particle swarm optimization (PSO) method for designing water distribution networks (WDNs). The optimization problem of looped water distribution networks is recognized as an NP-hard combinatorial problem which cannot be easily solved using traditional mathematical optimization techniques. In this paper, the concept of dynamic swarm size is considered in an attempt to increase the convergence speed of the original PSO algorithm. In this strategy, the size of the swarm is dynamically changed according to the iteration number of the algorithm. Furthermore, a novel mutation approach is introduced to increase the diversification property of the PSO and to help the algorithm to avoid trapping in local optima. The new version of the PSO algorithm is called dynamic mutated particle swarm optimization (DMPSO). The proposed DMPSO is then applied to solve WDN design problems. Finally, two illustrative examples are used for comparison to verify the efficiency of the proposed DMPSO as compared to other intelligent algorithms

Adaptive control of a vehicular platoon with unknown parameters and input variations

A switching adaptive control algorithm for automating connected vehicles in a rigid platoon pattern is proposed here. A second-order nonlinear model for the follower vehicles running on the highways is adopted and it is assumed that the parameters of the vehicles\u27s model, including the mass, aerodynamic drag and tire drag, are fully unknown and their values cannot be used in arriving at the control laws. Furthermore, some uncertainties and external perturbations are added to the model to consider the effects of always present modeling errors, un-modeled dynamics and external time varying perturbations on the vehicles. Besides, control input variations are inserted into the nonlinear model of the platoon to represent actuator fluctuations. Subsequently, a robust adaptive control scheme is established so that the asymptotic stability of each vehicle in the platoon is guaranteed, and this is demonstrated using the Lyapunov stability criterion. A novel spacing error variable is also introduced to achieve the global string stability for the whole platoon. Following a comprehensive mathematical analysis, a computer simulation example is presented to illustrate the effectiveness as well as the performance of the proposed control system