Mixed Logic Research Articles

Inferential-connexive mixed logics

Abstract In this article, we present a new type of connexive-like logics. We call them inferential-connexive mixed logics, as they satisfy inferential versions of the main four connexive principles: AT, AT’, BT and BT’. We focus first on some Strong-Kleene type of mixed and inferentially connexive logics that cannot be interpreted as truth-preserving, but that can receive other interpretations in terms to falsity-preservation and related features. We introduce afterwards the notion of inferential-connexive Boolean logic, and present some logics that fall in this ballpark. We also explain the relation between inferentially-connexive Boolean logics and some inferentially-connexive Strong-Kleene logics, and show how they can also be interpreted in epistemic (or attitudinal)-related terms.

Navigating Crisis and Democracy: Analyzing Mexico through the Neo-Weberian State and the TODO framework

This study uses the Neo-Weberian State (NWS) and TODO frameworks to examine Mexico’s public sector reforms and current challenges. Analyzing the trajectory of public administration reforms reveals a historical context of mixed logics, weak institutions, and limited capacity, further aggravated by recent democratic backsliding, dismantling, and austerity cuts. Next, based on the TODO framework, emphasizing turbulent environments, oscillating knowledge quality, domino-falling types of interdependence, and opposing solutions, we analyze the case of the migration crisis at the US-Mexico border as a way to exemplify current challenges faced by the Mexican public sector. The analysis exposes shortcomings in crisis management, highlighting political neglect, strained US-Mexico relations, and prolonged uncertainty for asylum seekers. Overall, the study underscores Mexico’s need to enhance systemic resilience governance. Findings contribute to the study of discourse on governance models, emphasizing the importance of adaptive frameworks for crisis management and democratic governance in the Global South.

Hybrid model predictive control for vehicle trajectory tracking with integrated attitude adjustment

This paper presents a vehicle trajectory tracking method that integrates attitude adjustment. The method utilizes the asymmetric adjustment of the damping of the adjustable damping shock absorber to lift the left and right vehicle body and carry out the attitude adjustment of the vehicle. Additionally, it actively tilts toward the inside of the curve during turning. In order to address the nonlinear constraints of damping asymmetry regulation and the mixed logic relationship between suspension asymmetry damping switching and left and right body lifting during body attitude regulation, a mixed logic dynamic system (MLD) for vehicle attitude adjustment is established. Subsequently, the vehicle trajectory tracking controller is designed using the hybrid model predictive control theory (HMPC), which integrates active steering control and attitude adjustment. The optimal control problem of hybrid systems is transformed into a hybrid integer quadratic programming problem and solved through finite time domain rolling optimization. The effectiveness of the proposed integrated controller is confirmed through Simulink simulation. Compared with pure tracking control and roll tracking control with zero roll angle as the control target, this controller demonstrates its ability to effectively track the reference trajectory and enhance the vehicle’s dynamic performance.

MLD Modeling and MPC-Based Energy Management Strategy for Hydrogen Fuel Cell/Supercapacitor Hybrid Electric Vehicles

Energy management strategies for hydrogen fuel cell hybrid electric vehicles (FCHEVs) are a key factor in achieving real-time vehicle energy optimization control, vehicle driving economy, and fuel cell durability. In this paper, for an FCHEV equipped with a fuel cell and supercapacitor, the quantitative information, logic rules, and operational constraints are transformed into linear integer inequalities according to its different operating modes, and the Hysdel language is used to establish its mixed logic dynamic model (MLD). Then, the energy management strategy based on model predictive control (MPC) is developed using the MLD model as the prediction model and the equivalent hydrogen consumption and the performance degradation of the fuel cell as the optimization performance indexes. Finally, under the World Light Vehicle Test Cycle, a joint simulation was carried out with Advisor and Simulink to verify the proposed strategy’s superiority by comparing it with the power following control strategy (PFCS) and the compound fuzzy control strategy (CFCS). The results show that the strategy not only ensures real-time FCHEV energy control, but also reduces hydrogen consumption by 10.98% and 1.98% and the number of start/stop times of a fuel cell by six and four, compared to PFCS and CFCS, respectively, which improves the economy of the whole vehicle as well as the durability of the fuel cell.

Fault‐tolerant control of current residual vector three‐phase four‐switch motor drive system based on MLD model

AbstractAiming at the problem of single‐phase switch tube open circuit fault in inverters, a current residual vector three‐phase four‐switch fault‐tolerant control strategy based on the mixed logic dynamic (MLD) model of permanent magnet synchronous motor (PMSM) drive system is proposed. Firstly, the MLD and three‐phase four‐switch mathematical models of the motor drive system are established and a calculation method of DC bus capacitance is proposed. Secondly, to improve the dynamic performance of the motor, an improved vector control based on the MLD model is proposed. Finally, by setting the threshold and dividing the area of the current residual vector, the accuracy of inverter fault diagnosis is improved, and the fast and smooth switching of the drive system after the fault is realized. Simulation and experimental results show that this strategy can effectively reduce the influence of calculation error and system noise, and has strong robustness for the change of motor speed and load.

Research on MLD Modeling and Predictive Control of Magnetically Coupled Resonant Bidirectional WPT System

The recent studies on magnetically coupled resonant bidirectional wireless power transfer (MCR-BWPT) systems disregard the challenges posed by nonlinearity, discrete switching action, and hybrid properties within the system. This research focuses on the D-LCL resonant compensation topology MCR-BWPT system. The switch tube’s switching state dictates the division of various working modes and the determination of the switching conditions between them. The coupling relationship between the continuous dynamic characteristics of the system and discrete events and the constrained conditions of the system are derived. The Hybrid System Description Language (HYSDEL) is used to build the Mixed Logic Dynamic (MLD) model of the system. The MLD model is employed as the prediction model, and the hybrid model predictive controller of the MCR-BWPT system is constructed according to the quadratic performance index. Finally, to verify the accuracy of the MLD model and the feasibility of the control strategy, the simulation model of the MLD model is established in MATLAB/Simulink. The study’s findings show that, in terms of response time at system startup and power fluctuation suppression, the approach put forward in this research performs better than both the conventional bilateral dual-phase-shift control strategy and the PQ-based bilateral power control strategy. The MCR-BWPT system can operate more steadily now that PQ’s bidirectional power control technique is in place. The system’s forward and reverse transmission efficiency is increased by 0.29% and 0.32% compared to the conventional bilateral dual-phase-shift control approach; the increases are 0.28% and 0.09%, each compared to the bilateral power control strategy based on PQ.

Practical hybrid model predictive control for electric pneumatic braking system with on-off solenoid valves

Accurate and rapid braking pressure regulation in electric pneumatic braking systems (EPBS) is vital to vehicle safety. Due to the switching behaviors of the on-off solenoid valves, the operation of the EPBS shows a hybrid nature with both continuous variables and discrete events, which raises the hybrid control problem. One of the possible solutions is to employ the hybrid model predictive controller with the mixed logical dynamical (MLD) model based on the linear approximation of the system dynamics. However, the nonlinearity and complexity of the EPBS make the MLD model obtained by linearizing the system equations directly require high storage and computing capacity. To address these issues, this article presents a practical hybrid model predictive controller based on the system dynamics simplified expressions considering the EPBS pressure variations caused by on-off solenoid valve states at the current sampling time and the last sampling time. The relationship between the pressure variations and the on-off solenoid valve states is first studied by the system mathematical model, followed by applying the mixed logic dynamical modeling approach to establish the hybrid model of the pressure continuous dynamics with discrete features of on-off solenoid valves. Based on these, a hybrid model predictive controller is formulated to solve the EPBS pressure control problem. The simulations and bench experiments are carried out to verify the controller. Besides, an existing model predictive control (MPC) controller is compared with the proposed controller. All the results demonstrate the effectiveness of the hybrid model predictive controller.

Piecewise affine model identification and predictive control for ultra-supercritical circulating fluidized bed boiler unit

In this paper, fully considering the form of the nonlinear model after linearization at the steady-state point, an improved subspace identification method based on the steady-state points' deviations data was proposed to identify piecewise affine model. Besides, the construction of the excitation signal in practical applications is fully considered. The identification results demonstrate that the method has better adaptability to strong nonlinear systems. The identification normalized root mean square error of each working condition is almost all less than 10%. On this basis, a framework that is widely applicable to complex system control is established combining with the mixed logic dynamic model. The canonical form realization is performed to transfer the local models into the same state basis. Predictive control was carried out on the boiler-turbine system of the 660-MW ultra-supercritical circulating fluidized bed unit based on the above framework. The results indicate the effectiveness of the framework.

Torsional oscillation suppression-oriented torque compensate control for regenerative braking of electric powertrain based on mixed logic dynamic model

This paper presents a novel torsional oscillation suppression-oriented torque compensate control for regenerative braking (TS-RTC) of electric powertrain, which is based on the gear-pair backlash and half-shaft flexibility-considered dynamic model of regenerative braking in electric powertrain (REP). According to the characteristics of transition from driving mode to regenerative braking mode (DM-to-RM), the dynamic models under different stages are transmitted into an equivalent mixed-logical dynamical (MLD) hybrid model. MLD-based hybrid braking system model and hybrid model predictive control are adopted to design the TS-RTC strategy, in which the torsional oscillation suppression-oriented cost function proved efficient in improving the regenerative braking performance during DM-to-RM process. Simulations and REP hardware in the loop test show that the fluctuation of half shaft torque are efficiently suppressed and the vehicle drivability is improved.

TOWARD THE RECOGNITION OF ARTIFICIAL HISTORY MAKERS

ABSTRACTArtificial intelligence is a historical discipline. This does not simply mean that its history can be written. It is historical on account of its recursive basis for action: its systems turn to prior beliefs—often through multiple steps or layers—to make recommendations for the present or predictions for the future. Using the two rooms approach of Alan Turing's imitation game, I highlight the potential for machine and human histories to be recognized via at least the idea of weak artificial intelligence. This recognition illuminates the mixed nature of the logic of history, combining deductions and endoxa. Finally, I note that illuminating and exploring this mixed logic of history signals a turn to historiographical metaphysics with Aristotelian features and, thus, the recognition of histories by professional historians as only part of a historiographical world. This signals that the recognition of machine and human history makers does not simply turn on the acknowledgement of imitation.

Layout Design of Row Decoder using Cadence

Abstract: Logic circuits, data transport circuits, and analogue to digital conversions all frequently employ decoders. For the line decoders, a mixed logic design approach incorporating transmission gate logic, pass transistor logic, and complementary metaloxide semiconductor (CMOS) technology is employed to achieve the desired performance and operation. A unique topology is proposed for the 2 to 4 decoders, which calls for a topology with fourteen transistors to reduce operating power and transistor count and a topology with fifteen transistors to achieve high power and low delay performance. For a total of four new designs, standard and inverting decoders are created for each situation. All of the suggested decoders have a low transistor count in comparison to their traditional CMOS architectures. Last but not least, a number of suggested solutions demonstrate a notable improvement in operating power and propagation latency, exceeding CMOS in virtually all instances

MLD–MPC for Ultra-Supercritical Circulating Fluidized Bed Boiler Unit Using Subspace Identification

Before carbon capture and storage technologies can truly be promoted and applied, and nuclear or renewable energy power generation can become predominant, it is important to further develop more efficient and ultra-low emission USC units on the basis of leveraging the strengths of CFB technology. In view of this complex system with strong nonlinearity such as the boiler-turbine unit of a thermal power unit, the establishment of a model that is suitable for control is indispensable for the operation and the economics of the process. In this study the form of the nonlinear model after linearization at the steady-state point has been fully considered and an improved subspace identification method, which is based on the steady-state point deviations data, was proposed in order to identify a piecewise affine model. In addition, the construction of the excitation signal in practical applications has been fully considered. The identification results demonstrate that this method has a better adaptability to strong nonlinear systems. The identification normalized root mean square errors of each working condition were almost all less than 10%. On this basis, a framework that is widely applicable to complex system control has been established by combining with the mixed logic dynamic (MLD) model. The canonical form realization was performed in order to transfer the local models into the same state basis. The predictive control was carried out on the boiler-turbine system of a 660-MW ultra-supercritical circulating fluidized bed unit that was based on the above framework. The results indicate that the predictive control performance is closely related to the setting value of the ramp rate and, therefore, prove the effectiveness of the framework.

Design of FinFET based low power, high speed hybrid decoder for SRAM

This paper proposes a novel FinFET based hybrid logic design for line decoders, which comprises of transmission gate logic (TGL), modified gate diffusion input (MGDI) logic and conventional NAND based FinFET logic. The 2–4 FinFET based decoder is designed using two topologies: (i) a 14- transistor topology for low power dissipation and lesser area and (ii) a 15-transitor topology for high-speed performance. Using the two topologies mentioned above, both inverting and non-inverting decoders of size 2–4 and 4–16 are designed. SPICE simulations of the proposed decoders are done at 45 nm CMOS and FinFET technologies and compared with different logic styles such as conventional logic, MGDI, mixed logic, and mixed MGDI logic at different frequencies with varying supply voltages and the proposed design outperforms other logic styles compared. The proposed FinFET hybrid decoder exhibits 6% and 77% lower power; 11.6% and 61.26% lower delay; 17% and 91.10% lower PDP respectively compared to the FinFET mixed decoder and CMOS hybrid decoder.

Spectrum and its Sequence Considered with Ordinary Colours and Mixing Logic

Spectrum and its Sequence Considered with Ordinary Colours and Mixing Logic

Spectrum and its Sequence Considered with Ordinary Colours and Mixing Logic

Spectrum and its Sequence Considered with Ordinary Colours and Mixing Logic

Simplifying Implications with Positive and Negative Attributes: A Logic-Based Approach

Concepts and implications are two facets of the knowledge contained within a binary relation between objects and attributes. Simplification logic (SL) has proved to be valuable for the study of attribute implications in a concept lattice, a topic of interest in the more general framework of formal concept analysis (FCA). Specifically, SL has become the kernel of automated methods to remove redundancy or obtain different types of bases of implications. Although originally FCA used only the positive information contained in the dataset, negative information (explicitly stating that an attribute does not hold) has been proposed by several authors, but without an adequate set of equivalence-preserving rules for simplification. In this work, we propose a mixed simplification logic and a method to automatically remove redundancy in implications, which will serve as a foundational standpoint for the automated reasoning methods for this extended framework.

Online Fault Diagnosis Method for Grid-Connected Inverters Based on Finite-Set Mixed Logical Dynamical Model Prediction

The grid-connected inverter is a key device in the renewable energy power generation system and large-scale energy storage system, which the operational stability and reliability are the basis for the efficient and safe application of electrical energy. A real-time fault diagnosis method of a three-phase for grid-connected application combining a mixed logic dynamic (MLD) model and finite control set model predictive control (FCS-MPC) is proposed. This paper not only realizes the open circuit fault diagnosis and location of the switching devices in the main power circuit, but also discusses the threshold issues and post-fault operations. The advantage of the proposed method is that it directly uses the control data and measurement signals of the controller without extra sensors and calculation, which will shorter the fault diagnosis time and occupy less calculation resource of the main processor. Simulation results illustrate the quickness of the fault identification and accurate position with robustness to the interference of the diagnosis method. Finally, the effectiveness of the diagnosis method was verified by a 1500W experimental prototype in a laboratory.

Non-financial Incentives for Retention of Health Extension Workers in Somali Region of Ethiopia: A Discrete Choice Experiment.

The study evaluated non-financial incentive packages to retain health extension workers in the Somali Region of Ethiopia using the Discrete Choice Experiment (DCE) technique, conducted among 66 health extension workers in 3 woredas (districts). The study used a mix of qualitative and quantitative methods in sequential order. Mixed logic regression modeling was used to determine the effect of different job attributes on the retention of the health extension workers, while Preference Impact Measure (PIM) was used to determine the combinations of preferred incentive packages to retain the health extension workers in their current workplace. Opportunity for continued education ranked first, 1.009 (0.655, 1.36), P = .000, followed by career advancement/opportunity for promotion, 0.321 (0.107, 0.534), P = .003, then supportive management 0.234 (−0.395, −0.073), P = .004. in terms of impact on retention. The most preferred incentive package for retention using the PIM model was opportunities for continued education after 3 years and always good availability of and access to amenities (running water, electricity, internet), which predicted a 77% retention rate if implemented. The identified proposed retention incentive packages will help in developing evidence-based incentive policies and strategies for the future retention of health extension workers in this region.

Virtual Current Coefficients Based Power Transistors Fault Diagnosis for Small Power EV-SRM Drives

Implementation of fault diagnosis for power converter is critical to improve the reliability of electric vehicle (EV) with switched reluctance motor (SRM) drive. Conventional fault diagnosis methods are usually suitable for a single chopping mode or a certain control strategy. To avoid the problem, a virtual current coefficient-based diagnosis method for power transistors is proposed considering different chopping modes, control strategies, and fault cases simultaneously. The multipoint current detection method is proposed to obtain more current information, which is capable of providing remarkable fault features. The sensor current variations under various fault conditions are analyzed. The fault is first detected by identifying the error between the real sensor current and the value calculated with the mixed logic model. Three virtual current coefficients are introduced to obtain the fault location principles. The fault types and fault power transistors are recognized according to the difference between the real current coefficients and the virtual current coefficients. The applications of the fault diagnosis method are extended with the proposed scheme. The method does not require complex calculation, and thus has a good dynamic performance. Experiments on a three-phase 12/8 SRM drive validate the effectiveness of the proposed fault diagnosis method.

A new parallel processing architecture for accelerating image encryption based on chaos

This study introduces a novel parallel processing architecture for accelerating image encryption based on chaos. In the proposed architecture, whole image data is split into partitions of particular size to create separate encryption threads. As the proposed cryptosystem employs several identical chaotic ciphers running concurrently and independently to process the partitions, it greatly leverages the degree of parallelism to some extent. A powerful output mixing logic based on an additional chaotic function, and simple exclusive-OR and shift operations is innovatively incorporated to ensure inter-partition diffusion. Since there is no dependency on previous data bytes in the introduced logic, blending operations applied on the outputs of independent encryption threads can be concurrently executed by exploiting loop-level parallelism to the extent allowed by data processing units available. The number of blending operations that should be carried out for an image is kept proportional to the partition size which also directly determines the number of separate encryption threads created. In order to measure encryption/decryption runtimes, the proposed architecture has been tested on two different multi-core CPUs, namely 4-core and 8-core. The obtained results show that the proposed cryptosystem parallelising sequential operations by introducing a multi-threaded encryption architecture is much faster than the base cipher and most of the other state-of-the-art algorithms. Having successfully passed various security tests, the proposed cryptosystem manifests its robustness against cryptographic attacks, and hence become evident that it is efficient for secure transmission.