Sensorless torque control scheme of induction motor for hybrid electric vehicle

In this paper, the sensorless torque robust tracking problem of the induction motor for hybrid electric vehicle （HEV） applications is addressed, Because motor parameter variations in HEV applications are larger than in industrial drive system, the conventional field-oriented control （FOC） provides poor performance. Therefore, a new robust PI-based extension of the FOC controller and a speed-flux observer based on sliding mode and Lyapunov theory are developed in order to improve the overall performance. Simulation results show that the proposed sensorless torque control scheme is robust with respect to motor parameter variations and loading disturbances. In addition, the operating flux of the motor is chosen optimally to minimize the consumption of electric energy, which results in a significant reduction in energy losses shown by simulations.     

Multidisciplinary hybrid hierarchical collaborative optimization of electric wheel vehicle chassis integrated system based on driver’s feel

The optimization design of chassis integrated system mainly involves steering, suspension and brake subsystems, which is essentially a multidisciplinary design optimization. This paper mainly researches the multidisciplinary optimization of the chassis integrated system for the electric wheel vehicle, from the view of ensuring a favorable feel for the driver. The dynamic models of differential steering system, brake system, active suspension system and vehicle are established. Then, taking the coupling relationship of the chassis subsystems into account, this paper proposes an evaluating index of driver’s ride comfort (Drc), which is composed of the steering road feel, brake feel and suspension ride comfort. In order to determine the weight coefficient in the quantization formula of Drc, the technique for order preference by similarity to ideal solution (TOPSIS) method is used to overcome the subjectivity in the selection. Based on these, a multidisciplinary hybrid hierarchical collaborative optimization (HHCO) method is proposed on the basis of the collaborative optimization (CO), which consists of a system level coordinator and a coupling analyzer to solve the problem of poor convergence and the low efficiency of CO method. The optimization results show that the proposed HHCO method has excellent computational efficiency and better convergence compared with the CO method, which can further improve the steering road feel and the drive ride comfort, on the premise of ensuring the brake feel and suspension ride comfort.     

Optimal control of neutral systems†

A method is presented whereby an optimal control may be obtained for a linear time-varying neutral system. The performance measure is quadratic with fixed finite upper limit. A form is derived for the coat functional, and the optimal control is obtained as the solution to a set of differential equations. A numerical technique for the solution of the equations is given and existence and uniqueness are proven.     

Bounded control of an underactuated biomimetic aerial vehicle—Validation with robustness tests

Flapping wing Micro Aerial Vehicles (FMAVs) have recently emerged as a promising challenge lying on the progress of the avionics technologies. The present paper deals with the development of simple control laws for an embedded implementation on a biomimetic MAV, aiming to control its attitude and position. The control laws are bounded, taking into consideration the amplitude bounds of the control angles characterizing the flapping wings movement. In order to validate the control laws, a simplified model having a simple wing kinematic parametrization and considering only the main aerodynamic forces and torques is proposed. The stability of the controller is shown in simulations using a diptera insect model. The robustness of the proposed controller is emphasized through different robustness tests. They concern mainly, model and aerodynamic parameters errors, and aim to validate the considered simplifications in the model.     

Mathematical model derivation of an unmanned circulation control aerial vehicle UC^2AV

This paper presents a system identification method to derive accurate mathematical models for an unmanned circulation control aerial vehicle(UC2AV)that account for the effects of circulation control(CC)on the vehicle dynamics.The X-plane flight simulator and the CIFER system identification software are utilized to first derive simulation models to verify and validate the proposed system identification methodology.This is followed by flight tests to derive mathematical models and stability derivatives for the aircraft with CC-on and CC-off.Flight tests indicate a nose down pitching moment effect induced by CC,which in turn alter the UAV trim values and dynamics.Analysis of the two sets of mathematical models reveal that CC changes the longitudinal trim values and improves the lateral maneuverability of the UAV.Verification experiments indicate an acceptable match between the derived models and UAV dynamics by calculating root mean square(RMS)error values and by quantifying the model predictive ability through calculating the Theil inequality coefficient(TIC).     

EVLibSim: A tool for the simulation of electric vehicles’ charging stations using the EVLib library

Electric Vehicles (EVs) are considered an efficient alternative to internal combustion engined ones, aiming to reduce global CO₂ emissions. In the last years, EVs are entering the market in an increasing pace. In contrast to conventional cars, EVs have a more complicated recharging procedure. Thus, the development of tools for the efficient simulation of the charging of large numbers of EVs is critical. In this vein, EVLibSim is a tool for the simulation of EV activities at a charging station level. EVLibSim unifies EVLib’s primary functions such as the charging and dis-charging of batteries, battery swapping, as well as parking/inductive charging. EVLib is a Java library that provides a simple, yet efficient framework for the management of a number of Electric Vehicle (EV) activities, at a charging station level, within a Smart Grid. EVLibSim provides a great variety of configuration options such as the types and number of chargers, the available energy, the waiting queues, etc. Furthermore, through plots and overview dashboards each user can supervise the operation of the tool in real time. Both EVLib’s and EVLibSim’s efficiency and scalability have been tested in realistic scenarios, while the correctness and safety of the code have been verified using state of the art tools. Finally, the user experience of the EVLibSim has been evaluated and improved through a detailed user evaluation.     

Impulsive control and synchronization of Chua’s oscillators

Impulsive control of a chaotic system is ideal for designing digital control schemes where the control laws are generated by digital devices which are discrete in time. In this paper, several new theorems on the stability of impulsive control systems are presented. These theorems are then used to find the conditions under which the Chua’s oscillator can be asymptotically controlled to the origin by using impulsive control. Given the parameters of the Chua’s oscillator and the impulsive control law, an estimation of the upper bound of the impulse interval is given. We also present a theory of impulsive synchronization of two Chua’s oscillators. A numerical example and simulation illustrates the effectiveness of the proposed result. Compared with the existing results, these results are less conservative.     

Optimal control of stochastic FitzHugh–Nagumo equation

This paper is concerned with the existence and uniqueness of solution for the optimal control problem governed by the stochastic FitzHugh–Nagumo equation driven by a Gaussian noise. First-order conditions of optimality are also obtained.     

Optimal discrete-time H∞/γ0 filtering and control under unknown covariances

New stochastic γ₀ and mixed H_∞/γ₀ filtering and control problems for discrete-time systems under completely unknown covariances are introduced and solved. The performance measure γ₀ is the worst-case steady-state averaged variance of the error signal in response to the stationary Gaussian white zero-mean disturbance with unknown covariance and identity variance. The performance measure H_∞/γ₀ is the worst-case power norm of the error signal in response to two input disturbances in different channels, one of which is the deterministic signal with a bounded energy and the other is the stationary Gaussian white zero-mean signal with a bounded variance provided the weighting sum of disturbance powers equals one. In this framework, it is possible to consider at the same time both deterministic and stochastic disturbances highlighting their mutual effects. Our main results provide the complete characterisations of the above performance measures in terms of linear matrix inequalities and therefore both the γ₀ and H_∞/γ₀ optimal filters and controllers can be computed by convex programming. H_∞/γ₀ optimal solution is shown to be actually a trade-off between optimal solutions to the H_∞ and γ₀ problems for the corresponding channels.     

Optimal control of the vibrations of a non-linear string†

A mathematical model for a vibrating non-linear string is constructed. An optimal control problem with a quadratic cost criterion is posed and necessary conditions for optimal controls are derived.     

Optimal control of a class of unconstrained bilinear systems†

The optimal control of a class of control unconstrained bilinear systems is considered. It is demonstrated that mere application of known necessary conditions of optimality is insufficient to solve the problem numerically. A technique overcoming this difficulty is proposed. It is demonstrated in an example involving optimal shut-down control of a nuclear reactor under xenon poisoning. The TPBVP is solved numerically using the variation of extremals method.     

Optimal control of viscous Burgers equation via an adaptive nonmonotone Barzilai–Borwein gradient method

An adaptive nonmonotone spectral gradient method for the solution of distributed optimal control problem (OCP) for the viscous Burgers equation is presented in a black-box framework. Regarding the implicit function theorem, the OCP is transformed into an unconstrained nonlinear optimization problem (UNOP). For solving UNOP, an adaptive nonmonotone Barzilai–Borwein gradient method is proposed in which to make a globalization strategy, first an adaptive nonmonotone strategy which properly controls the degree of nonmonotonicity is presented and then is incorporated into an inexact line search approach to construct a more relaxed line search procedure. Also an adjoint technique is used to effectively evaluate the gradient. The low memory requirement and the guaranteed convergence property make the proposed method quite useful for large-scale OCPs. The efficiency of the presented method is supported by numerical experiments.     

Optimal formation of fuzzy rule-base for predicting process’s performance measures

For various physical processes, especially those demanding high cost or operational time, it becomes crucial to have accurate predictions of their key performance measures based on given settings of different input parameters. Among other artificial intelligence based tools, fuzzy rule-based systems have also been widely used for this purpose. Widespread applicability of the rule-based systems has been restricted by lack of accuracy in the prediction results and inherent difficulties in different approaches that have been utilized for improving their prediction capabilities. The paper presents a two-stage approach for enhancing accuracy of prediction results. The first stage seeks best possible assignment of fuzzy sets of a response variable to the rules of a fuzzy rule-base, while the second stage looks for further improvement by adjusting shapes of the fuzzy sets of the response variable. For accomplishment of both of the stages, simulated annealing algorithm has been utilized and the approach has been practically applied on experimental data related to a turning process. The process has resulted in development of a rule-base that predicts with highly acceptable levels of accuracy.     

Optimal on–off control of refrigerated transport systems

This paper presents a hysteretic on–off control scheme with optimization algorithms for temperature regulation in refrigerated transport systems. A nonlinear dynamic refrigerated transport system model, which consists of a refrigeration unit and a cargo space, is developed. The model serves as an analytical tool for control design. An optimal on–off control strategy is developed based on the time domain analysis of the temperature oscillations. A cost function involving temperature variations from the set-point, energy consumption and average compressor on–off cycling frequency is introduced for minimization. Choices of weighting values in the cost function give the flexibility of the control approach to meet different requirements. Simulation examples are presented that demonstrate the ability and robustness of the proposed method in achieving tighter temperature regulation and higher system efficiency control in transport refrigeration systems. The simulations are augmented by experimental validation via a novel hardware-in-the-loop load emulation approach.     

Design of robotic arm’s action to imitate the mechanism of an animal’s consciousness

We are attempting to develop a system so that a user is able to let robots perform an intellectual action that has a healing and friendly feeling. Based on the development process of the actions and consciousness of animals, we constructed a structure model which connects consciousness and action hierarchically, built a valuation function for action selection, and developed software to control the action of a robot. This software is called Consciousness-Based Architecture (CBA). With it, our aim is to connect a user and robot as closely as possible and to allow smooth communications between them by developing an emotional system that takes notice of consciousness. In our system, the robotic arm’s finger is outfitted with a small Web camera, which allows the arm to recognize external information so that the robot can select various actions that comply with certain factors in the outside environment. Furthermore, by using the actuator of the robotic arm, the system we have built provides a correspondence between the robot’s internal states, such as the degree of rotation angle, and the outside temperature. In the present study, a motivation model which considers the outside environment and the internal states has been built into the CBA, and the behavior of the robotic arm has been verified.     

Estimation of the tire slip angle under various road conditions without tire–road information for vehicle stability control

This paper presents a tire slip angle estimator based on an Interacting Multiple Model (IMM) algorithm for vehicle stability control. The proposed algorithm is capable of estimating the tire slip angles under various road conditions without the prior knowledge of tire and road condition by only using on-board vehicle sensors. Instead of employing tire and road information, the proposed algorithm utilizes multiple numbers of model candidates to represent all aspects of vehicle motions under various road conditions. Each model candidate is a combination of lateral vehicle dynamics and transient/steady state tire dynamics. The proposed algorithm evaluates the fidelity of each model candidate to the current vehicle dynamics with probability. Moreover, in the proposed algorithm, multiple numbers of Kalman filters are embedded with these model candidates as process models. The final estimate of the proposed algorithm in each time step is a linear sum of the posteriori states from multiple embedded filters with the calculated probability as coefficients. The proposed estimation algorithm has been evaluated via vehicle tests. The tests have been conducted on dry asphalt and wet asphalt using a luxury passenger car equipped with a high-performance GPS for reference and data logging computer. The results have shown that the proposed estimator can successfully estimate tire slip angles with satisfactory accuracy under various road conditions     

Algorithm for Constructing an Analog of Plan’s Formula

We present an algorithm for constructing an analog of Plan’s formula, which is essential in obtaining a functional relation to the classical Riemann zeta-function. The algorithm is implemented in the Maple computer algebra system.     

Business ecosystem and stakeholders’ role transformation: Evidence from Chinese emerging electric vehicle industry

Nurturing an emerging industry’s business ecosystem always requires stakeholders’ efforts and role transformation. By systematically reviewing and studying the evolution of the Chinese electric vehicle industry, this paper constructs a three-dimensional theoretical framework including stages of business ecosystem lifecycle, stakeholder classification and functional roles, to analyse the transformation both of different stakeholders and their functional roles. The findings show that business ecosystem stakeholders have experienced role transformation following a mechanism defined as the ‘Triple Oscillation’ Model during the evolution of the emerging industry. These findings also help develop a conceptual model of agent-based system for business ecosystem evolution, which could be a starting point for further emerging industry study.     

Optimal design of sampled-data control systems by linear programming†

This paper is devoted to the design of digital compensators for a special class of fnite-settling-time, linear, sampled-data control systems which are required to track both step and ramp inputs with no steady-state error. A general procedure is given to design the digital compensator so that the system is optimum on the basis of the ITAE (integral of time-weighted absolute value of error) criterion, subject to the constraint that the peak overshoot of the system for a step input is less than a certain percentage. Linear programming is used to find the optimum solution. Suitable upper bounds are imposed on the variables involved so that the peak overshoot of the system for a unit step input may not exceed a given value. A method of incorporating a specification on the acceleration constant (K _a ) in the design is given, as also is a design example. For the case where finite settling time to a ramp input is not required, the design procedure is modified: a velocity constant (K _a specification is incorporated in the design in place of the K _a specification.