North China University of Technology

Zhang Y., Jin J., Huang L.

Conventional model predictive current control (MPCC) is a powerful control strategy for three-phase inverters that has the advantages of simple concept, quick response, easy implementation, and good performance. However, MPCC is sensitive to machine parameter variation, and the performance degrades substantially if a mismatch exists between the model parameters and real machine parameters. Model-free predictive current control (MFPCC) based on an ultralocal model, which uses only the input and output of the system without considering any motor parameters, has been proposed to solve this problem in this article. Since parameters are not required, the robustness of the control system is improved. However, conventional MFPCC based on an ultralocal model uses many control parameters, which increases the tuning work. Furthermore, the control performance is not ideal at low sampling frequency. This article proposes an improved MFPCC based on the extended state observer of PMSM drives that does not require motor parameters and needs less tuning work and lower computational time while achieving the better performance in terms of current harmonics, tracking error, and dynamic overshoot. The proposed method is compared to conventional MPCC and MFPCC, and the effectiveness is confirmed by the simulation and experimental results.

Qiu J., Tian Z., Du C., Zuo Q., Su S., Fang B.

With the development of Internet-of-Things (IoT) technology, various types of information, such as social resources and physical resources, are deeply integrated for different comprehensive applications. Social networking, car networking, medical services, video surveillance, and other forms of the IoT information service model gradually change people's daily lives. Facing the vast amounts of IoT information data, the IoT search technology is used to quickly find accurate information to meet the real-time search needs of users. However, IoT search requires using a large amount of user private information, such as personal health information, location information, and social relations information, to provide personalized services. Employing private information from users will encounter security problems if an effective access control mechanism is missing during the IoT search process. An access control mechanism can effectively monitor the access activities of resources and ensure that authorized users access information resources under legitimate conditions. This survey examines the growing literature on access control for an IoT search. Problems and challenges of access control mechanisms are analyzed to facilitate the adoption of access control solutions in real-life settings. This article aims to provide theoretical, methodological, and technical guidance for IoT search access control mechanisms in large-scale dynamic heterogeneous environments. Based on a literature review, we also analyzed the future development direction of access control in the age of IoT.

Wang Y., Feng Y., Zhang X., Liang J.

In this article, in order to optimize the dynamic performance of the permanent magnet synchronous motor (PMSM) speed regulation system, a nonlinear speed-control algorithm for the PMSM control systems using sliding-mode control is developed. First, a sliding-mode control method based on a new sliding-mode reaching law (NSMRL) is proposed. This NSMRL includes the system state variable and the power term of sliding surface function. In particular, the power term is bounded by the absolute value of the switching function, so that the reaching law can be expressed in two different forms during the reaching process. This method can not only effectively suppress the inherent chattering, but also increases the velocity of the system state reaching to the sliding-mode surface. Based on this new reaching law, a sliding-mode speed controller (SMSC) of PMSM is designed. Then, considering the large chattering phenomenon caused by high switching gain, an improved antidisturbance sliding-mode speed controller method, called SMSC + ESO method, is developed. This method introduces an extended state observer to observe the lumped disturbance and adds a feedforward compensation item based on the observed disturbances to the SMSC. Finally, simulation and experimental results both show the validity of the proposed control method.

Pan J., Zhang L., Wang R., Snášel V., Chu S.

Engineering design problems are usually large-scale constrained optimization problems, and metaheuristic algorithms are vital for solving such complex problems. Therefore, this paper introduces a new nature-inspired metaheuristic algorithm: the gannet optimization algorithm (GOA). The GOA mathematizes the various unique behaviors of gannets during foraging and is used to enable exploration and exploitation. GOA’s U-shaped and V-shaped diving patterns are responsible for exploring the optimal region within the search space, with sudden turns and random walks ensuring better solutions are found in this region. In order to verify the ability of the GOA to find the optimal solution, we compared it with other comparison algorithms in multiple dimensions of 28 benchmark functions. We found that the GOA has a shorter running time in high dimensions and can provide a better solution. Finally, we apply the GOA to five engineering optimization problems. The experimental results show that the GOA is suitable for many constrained engineering design problems and can provide better solutions in most cases.

Pang Z., Fan L., Sun J., Liu K., Liu G.

• A Kalman filter-based output tracking control system is presented. • A refined definition is given for stealthy false data injection attacks (SFDIAs). • Additive SFDIAs are designed to destroy system performance without being detected. • Effectiveness of an active data modification scheme to detect SFDIAs is checked. This paper investigates the design and detection problems of stealthy false data injection (FDI) attacks against networked control systems from the different perspectives of an attacker and a defender, respectively. First, a Kalman filter-based output tracking control system is presented, where stealthy FDI attacks are designed for its feedback and forward channels so as to destroy the system performance while bypassing a traditional residual-based detector. Second, to successfully detect such two-channel stealthy attacks, an active data modification scheme is proposed, by which the measurement and control data are amended before transmitting them through communication networks. Theoretical analysis is then carried out for both ideal and practical cases to evaluate the effectiveness of the detection scheme. An interesting finding is that the attacks designed based on a false model obtained from those modified data can remain stealthy. Finally, simulation results are provided to validate the proposed attack design and detection schemes.

Zuo Z., Yang X., Li Z., Wang Y., Han Q., Wang L., Luo X.

In this paper, we propose a progressive model predictive control scheme (PMPCS) by considering the cooperative control of local planning and path tracking for intelligent vehicles. An improved particle swarm optimization (IPSO) based model predictive control (MPC) method is developed to solve the planning and tracking problem. With the PMPCS, the total computational burden can be reduced sharply because of the seamless connection and mutual promotion between the optimization of two layers. Besides we also propose a novel planning algorithm, which can take traffic lights and overtaking time constraint into account. To solve these problems, we first combine model predictive control with artificial potential field (APF) to get a collision-free path by treating the time-varying safety constraints as the scope of the repulsive force and an asymmetrical lane potential field function. Furthermore, the pseudo velocity planning method is adopted to take traffic lights into account in the planning module. Simulation results show the reliability of the proposed algorithm and the advantages of the scheme compared with general hierarchical algorithm.

Xu S., Xue Y., Chang L.

Penetration of renewable energy in power systems has been increasing in the past decades in response to increased global electricity demand and concerns for the environment. Distributed energy resources (DERs) based on renewables have experienced rapid growth thanks to the incentive programs and broad-based participation. With the growing prevalence of DERs, the risk of grid instability and vulnerability increases due to the intermittent nature of renewable energy. At the same time, the voltage and frequency deviation problems emerge more often when the reverse power flow occurs under supply-demand imbalance in distributed power systems. Standards and grid codes have been issued for DER inverters to interconnect with the distribution grid. The updated standard and grid codes expect DERs to provide a variety of power system support functions in order to incorporate higher DER penetration and to maximize DER value to the grid. This paper provides an overview of the power system support functions from renewable DER inverters, which are categorized as: voltage regulation by active/reactive power control, frequency regulation by active power control, voltage ride-through, and frequency ride-through. The benefits and drawbacks of each algorithm are presented and compared with its predecessor, manifesting the logic in the evolution of the algorithms.

Wang Z., Zhang X., Rezazadeh A.

Excessive consumption of fossil fuels has led to depletion of reserves and environmental crises. Therefore, turning to clean energy sources is essential. However, these energy sources are intermittent in nature and have problems meeting long-term energy demand. The option suggested by the researchers is to use hybrid energy systems. The aim of this paper is provide the conceptual configuration of a novel energy cycle based on clean energy resources. The novel energy cycle is composed of a wind turbine, solar photovoltaic field (PV), an alkaline fuel cell (AFC), a Stirling engine and an electrolyzer. Solar PV and wind turbine convert solar light energy and wind kinetic energy into electricity, respectively. Then, the generated electricity is fed to water electrolyzer. The electrolyzer decomposes water into oxygen and hydrogen gases by receiving electrical power. So the fuel cell inlets are provided. Next, the AFC converts the chemical energy contained in hydrogen into electricity during electrochemical reactions with by-product (heat). The purpose of the introduced cycle is to generate electricity and hydrogen fuel. The relationships defined for the components of the proposed cycle are novel and is examined for the first time. Results showed that the output of the introduced cycle is 10.5 kW of electricity and its electrical efficiency is 56.9%. In addition, the electrolyzer uses 9.9 kW of electricity to produce 221.3 grams per hour of hydrogen fuel. The share of the Stirling engine in the output power of the cycle is 9.85% (1033.7 W) which is obtained from the dissipated heat of the fuel cell. In addition, wind turbine is capable of generating an average of 4.1 kW of electricity. However, 238.6 kW of cycle exergy is destroyed. Two different scenarios are presented for solar field design.

Pang Z., Luo W., Liu G., Han Q.

This brief addresses the cooperative output tracking control problem for a linear heterogeneous networked multi-agent system with random network-induced delays and packet dropouts in the feedback channel of each agent, which consists of one leader agent and multiple following agents. To compensate for adverse effects of those random communication constraints, an incremental networked predictive control scheme based on state observers is proposed. A necessary and sufficient condition is derived for the stability of the resulting closed-loop system, which is independent of random communication constraints. Experimental results on a networked multi-motor control test rig show the effectiveness and applicability of the proposed scheme, including a feature that zero steady-state output tracking errors can be achieved even for the case with plant-model mismatch.

Wang J., Luo X., Wang L., Zuo Z., Guan X.

A novel integral sliding mode control (ISMC) strategy, combining with a disturbance observer (DO) for vehicle-following systems, is presented in this article. The vehicle platoon includes a leading vehicle and multiple following vehicles subjected to unknown acceleration uncertainties. First, the ISMC based on DO and the constant time headway policy is constructed to realize the string stability of the whole vehicle platoon in a finite time, under the condition of zero initial spacing errors. The uncertainties of the vehicular system can be well estimated by extending DO even if the bounds of the uncertainties are not known exactly. In order to alleviate the chattering problem of the traditional ISMC, a continuous sliding surface including sign function is designed for the proposed ISMC strategy. Then, a modified constant time headway (MCTH) policy is proposed to overcome the requirement of zero initial spacing errors. In addition, the developed MCTH policy can effectively improve the string stability and safety of the vehicle platoon system. Finally, the effectiveness and advantages of the proposed algorithm are verified by the simulations and experiments.