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The purpose of this study is to propose a torque vectoring control system for improving the handling stability of distributed drive electric buses under complicated driving conditions. Energy crisis and environment pollution are two key pressing issues faced by mankind. Pure electric buses are recognized as the effective method to solve the problems. Distributed drive electric buses (DDEBs) as an emerging mode of pure electric buses are attracting intense research interests around the world. Compared with the central driven electric buses, DDEB is able to control the driving and braking torque of each wheel individually and accurately to significantly enhance the handling stability. Therefore, the torque vectoring control (TVC) system is proposed to allocate the driving torque among four wheels reasonably to improve the handling stability of DDEBs.

The proposed TVC system is designed based on hierarchical control. The upper layer is direct yaw moment controller based on feedforward and feedback control. The feedforward control algorithm is designed to calculate the desired steady-state yaw moment based on the steering wheel angle and the longitudinal velocity. The feedback control is anti-windup sliding mode control algorithm, which takes the errors between actual and reference yaw rate as the control variables. The lower layer is torque allocation controller, including economical torque allocation control algorithm and optimal torque allocation control algorithm.

The steady static circular test has been carried out to demonstrate the effectiveness and control effort of the proposed TVC system. Compared with the field experiment results of tested bus with TVC system and without TVC system, the slip angle of tested bus with TVC system is much less than without TVC. And the actual yaw rate of tested bus with TVC system is able to track the reference yaw rate completely. The experiment results demonstrate that the TVC system has a remarkable performance in the real practice and improve the handling stability effectively.

In view of the large load transfer, the strong coupling characteristics of tire , the suspension and the steering system during coach corning, the vehicle reference steering characteristics is defined considering vehicle nonlinear characteristics and the feedforward term of torque vectoring control at different steering angles and speeds is designed. Meanwhile, in order to improve the robustness of controller, an anti-integral saturation sliding mode variable structure control algorithm is proposed as the feedback term of torque vectoring control.

This paper aims to extend the previous contributions about data-driven control in aircraft control system from academy and practice, respectively, combining iteration and learning strategy. More specifically, after returning output signal to input part, and getting one error signal, three kinds of data are measured to design the unknown controller without any information about the unknown plant. Using the main essence of data-driven control, iterative learning idea is introduced together to yield iterative learning data-driven control strategy. To get the optimal data-driven controller, other factors are considered, for example, adaptation, optimization and learning. After reviewing the aircraft control system in detail, the numerical simulation results have demonstrated the efficiency of the proposed iterative learning data-driven control strategy.

First, considering one closed loop system corresponding to the aircraft control system, data-driven control strategy is used to design the unknown controller without any message about the unknown plant. Second, iterative learning idea is combined with data-driven control to yield iterative learning data-driven control strategy. The optimal data-driven controller is designed by virtue of power spectrum and mathematical optimization. Furthermore, adaptation is tried to combine them together. Third, to achieve the combination with theory and practice, our proposed iterative learning data-driven control is applied into aircraft control system, so that the considered aircraft can fly more promptly.

A novel iterative learning data-driven strategy is proposed to efficiently achieve the combination with theory and practice. First, iterative learning and data-driven control are combined with each other, being dependent of adaptation and optimization. Second, iterative learning data-driven control is proposed to design the flight controller for the aircraft system. Generally, data-driven control is more wide in our living life, so it is important to introduce other fields to improve the performance of data-driven control.

To the best of the authors’ knowledge, this new paper extends the previous contributions about data-driven control by virtue of iterative learning strategy. Specifically, iteration means that the optimal data-driven controller is solved as one recursive form, being related with one gradient descent direction. This novel iterative learning data-driven control has more advanced properties, coming from data driven and adaptive iteration. Furthermore, it is a new subject on applying data-driven control into the aircraft control system.

This new paper aims to combine the recent new contributions about direct data driven control and other safety property to form an innovative direct data driven safety control for aircraft flight system. More specifically, within the framework of direct data driven strategy, the collected data are dealt with to get the identified plant and designed controller. After reviewing some priori information about aircraft flight system, a closed loop system with the unknown plant and controller simultaneously is considered. Data driven estimation is proposed to identify the plant and controller only through the ratios of two correlation functions, computed from the collected data. To achieve the dual missions about perfect tracking and safety property, a new notion about safety controller is introduced. To design this safety controller, direct data driven safety controller is proposed to solve one constrain optimization problem. Then the authors apply the Karush–Kuhn–Tucker (KKT) optimality conditions to derive the explicit safety controller.

First, consider one closed loop system corresponding to aircraft flight system with the unknown plant and feed forward controller, data driven estimation is used to identify the plant and feed forward controller. This identification process means nonparametric estimation. Second, to achieve the perfect tracking one given transfer function and guarantee the closed loop output response within one limited range simultaneously, safety property is introduced. Then direct data driven safety control is proposed to design the safety controller, while satisfying the dual goals. Third, as the data driven estimation and direct data driven safety control are all formulated as one constrain optimization problem, the KKT optimality conditions are applied to obtain the explicit safety controller.

Some aircraft system identification and aircraft flight controller design can be reformulated as their corresponding constrain optimization problems. Then through solving these constrain optimization problems, the optimal estimation and controller are yielded, while satisfying our own priori goals. First, data driven estimation is proposed to get the rough estimation about the plant and controller. Second, data driven safety control is proposed to get one safety controller before our mentioned safety concept.

To the best of the authors’ knowledge, some existing theories about nonparametric estimation and tube model predictive control are very mature, but few contributions are applied in practice, such as aircraft system identification and aircraft flight controller design. This new paper shows the new theories about data driven estimation and data driven safety control on aircraft, being corresponded to the classical nonparametric estimation and tube model predictive control. Specifically, data driven estimation gives the rough estimations for the aircraft and its feed forward controller. Furthermore, after introducing the safety concept, data driven safety control is introduced to achieve the desired dual missions with the combination of KKT optimality conditions.

A high-precision gyroscope is an important tool for accurate positioning, and the amplitude stability and frequency tracking ability of the drive control system are important and necessary conditions to ensure the precision of micro-electro-mechanical systems (MEMS) gyroscopes. To improve the precision of MEMS gyroscopes, this paper proposes a method to improve the amplitude stability and frequency tracking ability of a drive control system.

A frequency tracking loop and an amplitude control loop are proposed to improve the frequency tracking ability and amplitude stability of the drive control system for a MEMS gyroscopes. The frequency tracking loop mainly includes a phase detector, a frequency detector and a loop filter. And, the amplitude control loop mainly includes an amplitude detector, a low-pass filter and an amplitude control module. The simulation studies on the frequency tracking loop, amplitude control loop and drive control system composed of these two loops are implemented. The corresponding digital drive control algorithm is realized by the Verilog hardware description language, which is downloaded to the application-specific integrated circuits (ASIC) platform to verify the performances of the proposed method.

The simulation experiments in Matlab/Simulink and tests on the ASIC platform verify that the designed drive control system can keep the amplitude stable and track the driving frequency in real time with high precision.

This study shows a way to design and realize a drive control system for MEMS gyroscopes to improve their tracking ability. It is helpful for improving the precision of MEMS gyroscopes.

The purpose of this paper is to elaborate a robust model‐based protective control algorithm for multi‐mass motor drives that are subjected to physical and safety constraints on their variables.

The algorithm relies on the off‐line computed maximum robust controlled invariant set or its approximation for the given drive system and imposed constraints. It can be used to patch any existing drive control scheme with a firm constraints satisfaction guarantee. The online patch implementation is actually a simple correction of the control signal computed with the existing control scheme, with a mandatory state observer.

Performance of the patch is tested on a two‐mass drive system in combination with classical two‐mass drive speed controllers – P+I and reduced state controller. All constraints violations that exist in the presented responses obtained without the protection patch are suppressed by using the patch which shows the effectiveness of the approach. A brief implementation analysis shows that a digital signal processor could be used for online implementation of the controller with the protective patch.

Robust invariant sets theory is efficiently and effectively used in a new application area – protection of multi‐mass electrical drives.

Ethernet continues to evolve as a viable fieldbus technology for industrial automation. This paper seeks to discuss the development of the Common Industrial Protocol (CIP) for Ethernet and standards with particular reference to time synchronisation, real time motion control and safety.

The CIP is introduced, with an overview of four network adaptations: CompoNet, DeviceNet, ControlNet, and EtherNet/IP. Developments in the EtherNet/IP implementation are discussed, along with key features. These include CIP Safety to meet the requirements for safety‐related control, CIP Sync for time synchronisation across CIP networks and CIP motion for real‐time closed loop motion control.

Standard, unmodified Ethernet will support time synchronisation, real time motion control and safety‐related applications with the CIP adaptation EtherNet/IP. The CIP enables complete integration of control with information, multiple CIP networks and internet technologies. CIP provides seamless communication from the plant floor throughout the enterprise, with a scalable and coherent architecture, incorporating functionality, such as safety, time synchronisation and motion control, hitherto only available with specialised or incompatible networks.

The implementations of CIP Sync, CIP Motion and CIP Safety and the corresponding standards provide functionality and flexibility not available from disparate specialist networks. The ability to fully integrate internet technologies and safety, synchronisation, motion and safety together is a distinguishing feature. Industrial Ethernet technologies vary in the ability to integrate to the same level of functionality and offer similar flexibility.

The development of CIP technology and the use of open standards are described. The opportunity to use the combination of an established automation protocol and standard, unmodified Ethernet provides potential cost benefits, flexibility, and innovative solutions, whilst providing integration, performance and cost advantages.

The aim of this paper is to undertake analysis and comparison of the closed‐loop and sensorless control systems sensitivity to the broken rotor for diagnostic purposes. For the same vector control system induction motor drive analysis concerning operation with the asymmetric motor, broken rotor fault handling and operation were investigated. Reliability, range of stable operation, fault symptoms and application of diagnosis methods based on control system variables utilization was analyzed.

Induction motor drive vector control system synthesis was applied using the multiscalar variables of the machine model with nonlinear feedback linearization applied to use classical cascaded PI controllers for the speed‐torque and flux decoupled control. Speed observer was applied for the rotor flux and rotor speed estimation for the sensorless control system synthesis.

Relative sensitivity of the state and control system variables to broken rotor fault based on experimental results for the closed‐loop and sensorless control systems is presented and compared. Drawbacks of using the MCSA analysis for the rotor fault diagnosis in the closed‐loop and sensorless control systems are pointed. Advantages and drawbacks of the state space estimators filtering characteristics in the sensorless control system are described.

Asymmetric IM motor drive handling and diagnosis. Broken rotor range diagnosis inconsistency using the popular MCSA method should be considered in the closed‐loop and sensorless control system of the induction motor drive. Depending on the IM motor drive application and the operation requirements the results can be used for asymmetric machine proper handling, choosing proper control system structure and control system variables for rotor fault early diagnosis.

Sensitivity of the state and control system variables to broken rotor fault based on experimental results for the closed‐loop and sensorless control systems is presented, which implies motor handling procedures and fault diagnosis.

The purpose of this paper is to design and test a linear predictive control algorithm with elements of fuzzy logic in the non-linear speed region of a two-mass system with a flexible shaft.

To compensate the non-linearity of friction in the low-speed region, the elements of the Q matrix have been retuned with the use of fuzzy logic. First, the influence of the Q matrix on the dynamics of the drive has been discussed. On the basis of these findings a fuzzy system has been developed.

It has been demonstrated that applying a relatively simple fuzzy system can reduce unwanted non-linear phenomena in the low-speed region; at the same time, the dynamics of the drive in the other regions is not deteriorated.

The solutions presented in the paper are original and have not been published so far. The influence of non-linear friction on the work of the drive in the low-speed region at different values of the matrix Q has been shown. Also, a novel system of online adjustment of the values of the Q matrix in a predictive speed controller has been introduced. Besides, the system has been compared against the classical predictive regulator.