Forward Control Research Articles

Model Reference Adaptive Control of an Independent Steer-by-Wire System: A Simulation Using a 14-Degree-of-Freedom Vehicle Model

This research delves into how Model Reference Adaptive Control (MRAC) can be applied in an independent Steer-by-Wire (SBW) system, utilising a detailed 14 Degrees of Freedom (DOF) full-vehicle model. This study is all about pushing forward vehicle dynamics and control using SBW technology. This study also has come up with some cutting-edge control algorithms that allow each wheel to be steered independently, which seriously boosts how manoeuvrable and responsive the vehicle is. Through simulations, the study shows that MRAC is a big improvement over traditional control methods where quantitative analysis shows that MRAC reduces yaw rate errors by up to 66.67% compared to Proportional-Integral-Derivative (PID) and 50% compared to Multi-order PID (MOPID). Additionally, in lateral acceleration and sideslip angle controls, MRAC demonstrates a similar reduction in errors, significantly outperforming PID and MOPID with errors maintained well below 10%, proving its worth in predictive control and real-time adaptability to various road conditions and driver intentions. The key finding from this study is that MRAC greatly enhances manoeuvrability and responsiveness compared to standard methods which offer flexibility according to the different driving scenarios. There are notable advancements in vehicle steering systems, which contribute to safer and more efficient driving. In essence, this work marks a significant step forward in automotive steering technology, opening the door to safer and more efficient modern vehicles.

Forward and backward control of an ultrafast millimeter-scale microrobot via vibration mode transition.

The ability to move backward is crucial for millimeter-scale microrobots to navigate dead-end tunnels that are too narrow to allow for turning maneuvers. In this study, we introduce a 15-mm-long legged microrobot, BHMbot-B, which is capable of rapid forward and backward locomotion through vibration mode transition control. By properly arranging the vibratory motions of the magnet, cantilever, and linkages, the pitching movement of the body and the vibration of the forelegs are in phase during the first-order vibration mode of the cantilever and in antiphase during the second-order mode, which induces the forward and backward movement of the microrobot. Owing to its outstanding load-bearing capacity, the BHMbot-B equipped with dual electromagnetic actuators, an onboard battery, and a control circuit, can execute complex running trajectories under wireless command. Its maximum untethered running speeds are evaluated as 18.0 BL/s (360 mm/s) in the forward direction and 16.9 BL/s (338 mm/s) in the backward direction.

On-line evaluation of moisture transfer properties for a feed-forward control of a wood drying kiln with a mechanistic model

Kiln operators are forced to rely on their own experience and expertise when adapting standard drying schedules to tackle changing situations or to better suit their needs. The online tuning of a mechanistic model and its use as forward control is therefore proposed to address the current lack of tools. An inverse analysis of the drying kinetics of wooden boards dried in an industrial kiln is carried out to determine the moisture transfer properties of the boards. The values obtained by the inverse method are found to be relatively close to those obtained by direct measurement. The mechanistic model is then used with these input values to simulate the drying of a stack of boards to find the best drying strategy to meet the objectives. This work focuses on achieving a compromise between quality and time. Several difficulties were encountered in developing this approach for a semi-industrial dryer, and some recommendations are made for developing this innovative strategy further.

Output speed control for hydro-mechanical continuously variable transmission of tractor.

In order to improve the speed stability of tractors equipped with hydro-mechanical continuously variable transmission (HMCVT) during field operations, the speed regulation characteristics, torque characteristics, and power diversion characteristics of HMCVT are analyzed. And a comprehensive control strategy for HMCVT output speed is proposed by analyzing the factors affecting the fluctuation of output speed, which combines engine speed control and displacement ratio control of hydraulic speed control system. This strategy adopts fuzzy control to regulate the engine speed to maintain the stability of engine operation. Moreover, adopting feed forward compensation control for speed compensation enhances the anti-interference ability of the hydraulic speed control system. And combined with model predictive control, adjust the swash plate swing angle of the variable pump to reduce the fluctuation of HMCVT output speed. By establishing joint simulation model, the effectiveness of the control strategy was verified using tractor acceleration mode and step load disturbance mode. The results show that the strategy can reduce the fluctuation rate of engine speed and impact degree, shorten the adjustment time, and improve the stability of tractor operating speed.

基于H无穷状态反馈控制的插秧机曲线路径跟踪控制器研究

The accuracy of curved path-tracking for headland turning of transplanters is crucial to maintaining the row spacing precision required for rice planting. To address this issue, a method based on H-infinity state feedback control is proposed. In this method, the requirement of robustness is transformed into linear matrix inequalities (LMIs) to optimize the gain coefficients of the control law. The simulation test show that this method outperforms the Linear Quadratic Regulator (LQR) when facing uncertain parameters (longitudinal speed and cornering stiffness) and path curvature disturbance. In addition, the field test results show that when the transplanter tracks a 1/4 circular arc path with a radius of 2 meters, the mean value of the absolute lateral error and the absolute heading angle error using this controller are 0.029 m and 3.69°, respectively. The maximum absolute lateral error is 0.072 m, and 64% of the absolute lateral error are less than 0.04 m, meeting practical requirements. Compared with the LQR controller with feed forward control, the mean value of the absolute lateral error is reduced by 36%. This method meets the accuracy and robustness requirements for unmanned rice transplanter turning at the headland.

Analytical design of modified Smith predictor for second-order stable time delay plants incorporating a zero

Simplified control tuning not only enhances engineers' proficiency in control theory and its application but also contributes to their skill development. This study focuses on the control of stable second-order plus time delay (SOPTD) plants incorporating a zero, by employing a modified Smith predictor structure. A forward path PID controller and a PID controller with a lead/lag filter in the feedback path contribute to the proposed control system. The PID controller determines the set-point tracking. The load disturbance rejection is influenced by both the PID and lead/lag filter. Each controller is simply designed using pole placement, while considering a tuning parameter to make a balance between performance and robustness. Filtering of the set-point signal is implemented to enhance its response. To assess the effectiveness of the proposed technique, the study involves examining a SOPTD plant and either a negative or a positive zero. Simulation and comparison analysis show that the proposed controller is appropriate for industrial usage since it quickly tracks the set-point and efficiently rejects disturbances, resulting in a smooth control signal. Furthermore, robustness tests reveal its satisfactory degree of robustness against model parameter uncertainties. In summary, the proposed approach is straightforward and outperforms recently published design methodologies in terms of both performance and robustness.

Analysis on the ‘Jul.20’ extreme rainstorm and flood control countermeasures in Zhengzhou, China

ABSTRACT The Jul.20 extreme rainstorm (July 20, 2021) and flood disaster were the most serious urban flood disaster in Zhengzhou, the capital city of Henan Province, China. The Jul. 20 extreme rainstorm had both extreme and unpredictable features, during which both single-day and 3-day cumulative rainfall exceeded the historical records. First, the theoretical analysis methods are proposed, which include rainstorm anomaly analysis and the construction of a rainstorm frequency calculation model. Second, the characteristics of rainstorm frequency and recurrence, spatial and temporal distribution, and formation mechanism are analyzed. Third, urban flood disasters and waterlogging distribution are studied. The studied results show that the coupling actions of typhoons, topography, and urban rain island effect are the natural causes that result in extreme rainstorm weather processes. The results also show from the investigations that poor urban drainage infrastructure, low flood control criteria, shortage of flood emergency plans, and management are human factors. Finally, the paper puts forward flood control countermeasures.

Research on approximate optimal energy management and multi-objective optimization of connected automated range-extended electric vehicle

In order to attain the optimal allocation of energy between auxiliary power unit (APU) and battery of the connected automated range-extended electric vehicle, from a multi-scale perspective, an Approximate Optimal Energy Management Strategy (AOEMS) has been proposed. Firstly, a composite determination method was designed based on prediction and parameter identification to divide the operating condition types, which could be as an operating condition prediction and feed forward control method to determine the approximate optimal power distribution between APU and battery. This method keeps APU operating at the optimal operating point/area as much as possible without predicting the accurate vehicle speed sequence. Then, an adaptive method based on V2X information was used to adjust the key threshold parameters in real-time using a fuzzy logic controller which reduces the algorithm complexity with prediction and division of the operating conditions types, which has significantly improved the robustness and overall performance of the optimization. Finally, the simulation and experimental results thoroughly indicated that the proposed AOEMS can better balance the performances, as anticipated, enhancing economy, reducing emissions, and extending battery lifewere effectively maintained in equilibrium.

Design of a low-profile bi-directional radiated Fabry-Perot cavity antenna with independent forward and backward radiation based on metasurface technique.

This paper introduces a novel Fabry-Perot cavity (FPC) antenna design based on metasurface technique to achieve bi-directional radiation with independent forward and backward beam control capability and a low-profile configuration. Two pieces of partially reflective metasurface (PRMS) based on receiver-transmitter architecture with independent control of transmission and reflection phases are designed to serve as the upper and lower layers of the FPC antenna, respectively. By manipulating the transmission phase distribution of the two pieces of PRMS, designable independent multi-beam bi-directional radiation patterns can be achieved. For validation, two FPC antennas based on the proposed configuration are designed with different bi-directional radiation patterns. Proved by simulated results, Antenna 1 can achieve forward dual-beam and backward single-beam radiation simultaneously with a return loss of less than -10 dB at 10.4 GHz. The two beams of forward radiation point in the -45° and 35° directions, respectively, with gains of 7.42 dBi and 7.70 dBi. The gain of the single beam of backward radiation is 10.82 dBi. Antenna 2 can achieve a four-beam radiation pattern with both forward and backward dual beams. The beam directions of the four beams are -153°, -44°, 37°, and 146°, respectively. The gains in each direction are 5.45 dBi, 6.63 dBi, 5.97 dBi, and 5.22 dBi, respectively. The overall profile is 23.72 mm (0.81 λ) for both antennas. The prototype of Antenna 1 is fabricated and measured. The results are in good agreement with the simulated counterparts, which demonstrates the feasibility of the proposed design methodology.

An event triggered control scheme for enhanced production of Escherichia coli and biomass concentration during fed-batch cultivation

Control of a bioprocess is a challenging task mainly due to the nonlinearity of the process, the complex nature of microorganisms, and variations in critical parameters such as temperature, pH, and agitator speed. Generally, the optimum values chosen for critical parameters during Escherichia coli (E.coli) K-12fed-batch fermentation are37 ᵒC for temperature, 7 for pH, and 35 % for Dissolved Oxygen (DO). The objective of this research is to enhance biomass concentration while minimizing energy consumption. To achieve this, an Event-Triggered Control (ETC) scheme based on feedback-feed forward control is proposed. The ETC system dynamically adjusts the substrate feed rate in response to variations in critical parameters. We compare the performance of classical Proportional Integral (PI) controllers and advanced Model Predictive Control (MPC) controllers in terms of bioprocess yield. Initially, the data are collected from a laboratory-scaled 3L bioreactor setup under fed-batch operating conditions, and data-driven models are developed using system identification techniques. Then, classical Proportional Integral (PI) and advanced Model Predictive Control (MPC) based feedback controllers are developed for controlling the yield of bioprocess by manipulating substrate flow rate, and their performances are compared. PI and MPC-based Event Triggered Feed Forward Controllers are designed to increase the yield and to suppress the effect of known disturbances due to critical parameters. Whenever there is a variation in the value of a critical parameter, it is considered an event, and ETC initiates a control action by manipulating the substrate feed rate. PI and MPC-based ETC controllers are developed in simulation, and their closed-loop performances are compared. It is observed that the Integral Square Error (ISE) is notably minimized to 4.668 for MPC with disturbance and 4.742 for MPC with Feed Forward Control. Similarly, the Integral Absolute Error (IAE) reduces to 2.453 for MPC with disturbance and 0.8124 for MPC with Feed Forward Control. The simulation results reveal that the MPC-based ETC control scheme enhances the biomass yield by 7 %, and this result is verified experimentally. This system dynamically adjusts the substrate feed rate in response to variations in critical parameters, which is a novel approach in the field of bioprocess control. Also, the proposed control schemes help reduce the frequency of communication between controller and actuator, which reduces power consumption.

Statistically consistent inverse optimal control for discrete-time indefinite linear–quadratic systems

The Inverse Optimal Control (IOC) problem is a structured system identification problem that aims to identify the underlying objective function based on observed optimal trajectories. This provides a data-driven way to model experts’ behavior. In this paper, we consider the case of discrete-time finite-horizon linear–quadratic problems where: the quadratic cost term in the objective is not necessarily positive semi-definite; the planning horizon is a random variable; we have both process noise and observation noise; the dynamics can have a drift term; and where we can have a linear cost term in the objective. In this setting, we first formulate the necessary and sufficient conditions for when the forward optimal control problem is solvable. Next, we show that the corresponding IOC problem is identifiable. Using the conditions for existence of an optimum of the forward problem, we then formulate an estimator for the parameters in the objective function of the forward problem as the globally optimal solution to a convex optimization problem, and prove that the estimator is statistical consistent. Finally, the performance of the algorithm is demonstrated on two numerical examples.

Adaptive command filtered control for a class of nonlinear time delay systems with extreme learning machine

AbstractIn this paper, an extreme learning machine (ELM)‐based adaptive command filtered control method is investigated for a class of strict feedback nonlinear systems with unknown external disturbances and time delay. To begin with, the original system state equation is transformed into a new form on account of coordinate transformation. Subsequently, an ELM is adopted to approximate unknown functions which exist in the whole system states, without any prior knowledges of the ideal weight vectors and approximation errors. Secondly, a command filter is developed for the system under consideration, which can avoid the probem of “explosion of complexity” caused by repeated derivation of virtual control signals in traditional backstepping control. Meanwhile, error compensation signals are designed to conquer the shortcoming of a dynamic surface control (DSC) method. The combination of ELM and command filter technique has been used to construct corresponding controllers and adaptive laws. Effective handling of the impact of time delay terms is ensured through designing a novel Lyapunov–Krasovskii functional. The proposed strategy guarantees boundedness of all signals in the closed‐loop system and the tracking error asymptotically converges to a compact set around the origin. In the end, two continuous stirred tank reactors (CSTRs) are taken as example to further verify the efficiency of the put forward control method.

Analysis, Simulation, and Experiments of Dynamics and Control of a Hydrostatic Wind Turbine Under Partial Load

Abstract Kω2 control, also called torque control, is a popular method for maximizing wind turbine power. For hydrostatic wind turbines, torque control becomes pressure control with pc=K'ω2 because pressure is proportional to torque. Inverse Kω2 control is an alternative approach using rotor speed control with pc=(p/K')1/2. This work analyzes the dynamics of hydrostatic wind turbines using forward and inverse Kω2 control with P-, PD-, PI-, and PID-control for feedback. Dimensionless, linearized models are used. Analysis shows that the mechanical rotor dynamics are much slower than the hydrostatic transmission dynamics and that frictional and leakage losses are negligible. Linear perturbation of the nonlinear model reveals that the closed-loop control is not in Evan's form, so that closed-loop poles and zeros both vary with the loop gain. Pole and zero root locus analysis shows how systems responses change with controller gains. Both control approaches require derivative controller action to sufficiently dampen their responses; both are also fundamentally limited in speed of response by a slow stable pole regardless of controller loop gains. Nonlinear system simulation shows that both control approaches track the maximum power point with nearly identical transient behavior and have nearly identical power losses when using suboptimal values of the control law gain, K. Pressure control has a gain margin of infinity and a phase margin of 99.3 degrees, while speed control has a gain margin of 22.4 dB and a phase margin of 73.8 degrees showing that pressure control is more robust than speed control. Experiments using the power regenerative hydrostatic test stand at the University of Minnesota show that the control approaches have different transient responses but capture comparable power under steady and turbulent conditions.

Three-phase Electric Motor Control with a Manual Forward Reverse Control System Equipped with a Delay Timer

The control of three-phase electric motors with manual forward and reverse control systems equipped with off-timers (TOF) is a production solution with a simple structure and relatively low cost compared to other systems. Three-phase induction motors typically work via electromagnetic induction from the stator winding to the rotor, making them the preferred choice in both large and small industries due to their accommotivity and efficiency. The purpose of this study was to determine and analyze the control of a three-phase electric motor with a manual back and forth control system equipped with a delay timer. The research method used is secondary data analysis from various relevant and valid sources. The results showed that the manual back and forth control system with TOF is very effective in moving production equipment efficiently and reliably. The implications of this study show that with current technological developments, the use of three-phase electric motors with manual back and forth control systems equipped with TOF has become very important in improving operational efficiency and effectiveness in the industrial world.

Energy-optimal car-following model for connected automated vehicles considering traffic flow stability

To reduce energy consumption and transportation emissions during car-following behavior on highways, we propose a car-following model for connected automated vehicles (CAVs). This new model considers spacing variation of the surrounding vehicles located immediately upstream and downstream. We optimize the key parameter of forward control weight of the proposed CAV model to stabilize traffic flow and ensure stable conditions. Then simulation experiments are conducted to validate the effectiveness of our proposed CAV model in enhancing traffic flow stability and energy-saving in mixed traffic consisting of both CAVs and regular vehicles (RVs). Results show that traffic flow controlled by the proposed CAV model is less affected by disturbances. The increase of CAV penetration rates can gradually improve stability of the mixed traffic flow. CAVs equipped with our proposed model can effectively reduce energy consumption and transportation emissions, which decrease with an increase of CAV penetration rates under constant speed conditions. When CAV penetration rate reaches 100 %, the average reduction of energy consumption, CO2 emissions, and NOx emissions at various speeds reach a peak value of 22.15 %, 31.00 %, and 56.41 %, respectively. Speed also has significant influence on energy consumption and emissions, with potential reductions when speed falls within an appropriate range.

Integrated management of abatement technology investment and resource extraction

As the need for increased renewable energy generation to meet climate goals grows, so does the demand for critical minerals in the industrial sector. This raises concerns about the availability of supply and the reliability of investment in critical minerals. Based on this, the study proposes an analytical framework for the integrated management of mineral extraction and renewable energy investments. Different from the previous strategy of separate management, this study has established an integrated model that utilizes new energy technology as the downstream application of emission reduction technology. It also utilizes copper, zinc, aluminum, rare earth elements, and other materials as the upstream raw material supply. In terms of minimizing costs, the entire supply chain process is optimized to achieve an empirical case. In addition, considering the significant uncertainty in the process of reducing emissions from new energy technologies, this study also incorporated a forward control stochastic programming method to model and solve it. We obtained confidence intervals for optimal technological investment paths and metal mining paths under various scenarios. Our findings indicate that: (1) Biomass, as a renewable energy technology with the lowest resource demand, should be prioritized for development. However, there is significant uncertainty surrounding the installed capacity of photovoltaics. (2) Copper ore reserves have little impact on the development of renewable energy technologies, while zinc ore and aluminum ore have a greater impact on wind energy and photovoltaics, respectively. (3) By optimizing the cut-off ratio of raw ore under a specific amount of ore storage, we can ensure the availability of materials needed for downstream energy technology.

Development of a novel monolithic compliant Lorentz-force-driven XY nanopositioning system

A novel monolithic compliant Lorentz-force-driven XY nanopositioning system (MCLNS) is designed, analyzed, and experimentally assessed with the aim of high-resolution positioning across a large workspace. A double-symmetric Lorentz-force actuator (DSLA) with the benefits of zero friction, high thrust, and large stroke is proposed to generate the actuation force. Correspondingly, a monolithic four-prismatic parallel compliant mechanism (4P-PCM) is exploited to transmit the actuation motion to the central platform and minimize the parasitic motion. The unique integration of four DSLAs and one 4P-PCM make the proposed MCLNS possess compact structure and stable performance. The characterization of the MCLNS is formulated by a specially established analytical model and validated by finite-element analysis simulation and experimental tests. Experimental studies show that the workspace of the MCLNS prototype is large than 0.87 × 0.87 mm2 and the positioning resolution of the MCLNS prototype is better than 9 nm. By means of a nonlinear forward proportional integral derivative control strategy, the maximum contouring error of the MCLNS is maintained within 2.7% while tracking a 1257 μm s−1 circular trajectory.

Performance Analysis of Positive Output (P/O) Push-Pull Switched Capacitor Converter for High Power Density Applications

The micro-power-consumption technique requires high power density DC/ DC converters and power supply sources. In this research, a PI and Fuzzy Logic Controllers for an elementary circuit of positive output (P/O) push-pull switched capacitor converter has developed for high power density applications with high sustainability under enormous line and load disturbances. The voltage lift technique is a popular application in electronic circuit design. The power converter performs DC-DC step-up voltage conversion with high efficiency, high power density and cheap topology in a simple structure. The proposed converter combines both switched-capacitor and voltage lift techniques. Referable to the time varying and switching nature of the power electronic converter their dynamic behavior becomes highly nonlinear. Conventional controllers are incapable of providing excellent dynamic performance and hence the fuzzy logic controller can be used as a feed forward controller for controlling power electronic converters. The control algorithm is developed to ensure tracking of the reference voltage and rejection of system disturbances by successive measurements of the converter output voltage at certain time instants within a conduction period. The simulation of PI and Fuzzy logic controls have been carried out using MATLAB/Simulink software to evaluate the controller’s performances. Keywords: Luo converter, DCDC converter, PI Controller, Fuzzy Controller.

SCFI: Efficient forward fine-grained control flow integrity based on coarse-grained ISA extensions

Code reuse attack (CRA) is a severe threat to computer systems. To mitigate this threat, control-flow integrity (CFI) was proposed to restrict control-flow transfers. Processor vendors developed Instruction Set Architecture (ISA) extensions to enforce forward CFI on processors, such as Indirect Branch Tracking (IBT) developed by Intel and Branch Target Identification (BTI) developed by ARM. However, these extensions are coarse-grained and unable to provide enough security protection.We combine existing coarse-grained ISA extension with novel software modifications and propose a new fine-grained forward CFI implementation called Slot-based CFI (SCFI). SCFI consists of two software modifications: Slot Policy and ID Policy. Slot policy utilises lower bits of code address as labels to implement fine-grained CFI. ID Policy provides multi-label support to solve the destination equivalence problem. SCFI strengthens security by improving coarse-grained ISA extension to fine-grained CFI (improving Average Indirect Targets Allowed (AIA) from 752 to 6.24). SCFI costs negligible performance overhead (on average 0.78% in SPEC2006). It also has good performance in complex programs (1.12% in 471.omnetpp and 1.79% in 483.xalancbmk). In addition, SCFI only needs lightweight software instrument without hardware modification and supports complex control-flow graphs.

Fast Multi-User Searchable Encryption with Forward and Backward Private Access Control

Untrusted servers are servers or storage entities lacking complete trust from the data owner or users. This characterization implies that the server hosting encrypted data may not enjoy full trust from data owners or users, stemming from apprehensions related to potential security breaches, unauthorized access, or other security risks. The security of searchable encryption has been put into question by several recent attacks. Currently, users can search for encrypted documents on untrusted cloud servers using searchable symmetric encryption (SSE). This study delves deeply into two pivotal concepts of privacy within dynamic searchable symmetric encryption (DSSE) schemes: forward privacy and backward privacy. The former serves as a safeguard against the linkage of recently added documents to previously conducted search queries, whereas the latter guarantees the irretrievability of deleted documents in subsequent search inquiries. However, the provision of fine-grained access control is complex in existing multi-user SSE schemes. SSE schemes may also incur high computation costs due to the need for fine-grained access control, and it is essential to support document updates and forward privacy. In response to these issues, this paper suggests a searchable encryption scheme that uses simple primitive tools. We present a multi-user SSE scheme that efficiently controls access to dynamically encrypted documents to resolve these issues, using an innovative approach that readily enhances previous findings. Rather than employing asymmetric encryption as in comparable systems, we harness low-complexity primitive encryption tools and inverted index-based DSSE to handle retrieving encrypted files, resulting in a notably faster system. Furthermore, we ensure heightened security by refreshing the encryption key after each search, meaning that users are unable to conduct subsequent searches with the same key and must obtain a fresh key from the data owner. An experimental evaluation shows that our scheme achieves forward and Type II backward privacy and has much faster search performance than other schemes. Our scheme can be considered secure, as proven in a random oracle model.