Automobile Cruise Research Articles

A synergetic strategy of automobile intelligent cruise system based on fuzzy control adopting hierarchical structure

To improve automobile travel safety and relieve the intension of driving fatigue, a synergetic strategy on the throttle and brake combined control of automobile cruise system is proposed based on fuzzy control theory. A hierarchical control structure, including the upper fuzzy controller and the lower model match controller, is designed for integrated control function. The upper controller consists of the two input variables, that is, the deviation of the theoretical safe distance and the relative distance and the relative velocity between the host car and the preceding vehicle, and the single output variable, that is, the excepted acceleration of host car. The lower controller has achieved the fast compensation of excepted acceleration by adopting parallel feedforward and feedback compensator to input into the inverse dynamics model of automobile cruise system. Using MATLAB/Simulink, the control function on the proposed synergetic strategy is validated for different working cases. The results show that the synergetic strategy possesses an integrated capability involved automated stop & go control, and following the preceding car to prevent rear-end collision, and the constant velocity cruise whether the driving conditions of the city road or expressway.

Antlion optimizer tuned PID controller based on Bode ideal transfer function for automobile cruise control system

Abstract Automobile cruise control reduces driver fatigue and ensures traffic safety by heavily relying on ICT and control engineering. A number of cruise control schemes are expected to be designed for proper safety management of vehicles in automobile design sector. Due to boosting road crowds, there is a new demand in developing automation of cruise control. The successfulness of automation of cruise control is heavily dependent on the efficient design of feedback control system. The use of evolutionary algorithms in designing feedback control of automobile cruise control system has reported in recent literature. It involves the communication of traffic data captured by sensor with actuator of the vehicle. The literature still lacks use of recently developed evolutionary algorithms for cruise control that could leverage road safety by tuning the control parameters. This paper presents the design of robust PID controller for an automobile cruise control system (ACCS). A linearized version of the cruise control system has been studies as per the dominant characteristics in closed loop system. The PID controller is designed as per Bode ideal transfer function to ensure robustness and formulated as an optimization problem. The gain parameters of the designed PID controller are tuned by ant lion optimizer (ALO) algorithm such that the proposed compensated system depicts the Bode ideal reference model. A comparison of this approach, a state space method, classical PID, fuzzy logic, genetic algorithm is presented. Numerical simulations shows that the ALO tuned PID controller based on bodes ideal model has better performance in terms of settling time, rise time, maximum overshot, peak time and steady state error. The performance analysis has performed by time domain analysis and frequency domain analysis. The robustness of the system is evaluated by considering sensitivity, complimentary sensitivity and controller sensitivity function. Further, the disturbance rejection behavior is studied for the proposed system. The analysis result reveals that the proposed ALO based PID controller with Bode ideal model for ACCS performs better than other recently published methods. All the simulations are carried out in Simulink/Matlab environment.

PID Controller Design for Cruise Control System using Particle Swarm Optimization

This paper presents a design of a Proportional-Integral-Derivative (PID) controller for automobile cruise controlsystem. The parameters of the PID controller, which are the proportional ( ), derivative ( ) , and integrator ( ), have beenselected using Particle Swarm Optimization (PSO) algorithm. In this study, the overall system performance has beencompared with other predesigned controllers (conventional PID, Fuzzy logic PID, state space, and Genetic algorithm basedPID controller). The simulation result illustrates that PSO based PID controller gives the best response in terms of settlingtime, rise time, peak time, and maximum overshot. The robustness analysis shows that the system is robust despite thedeviations in some of the system parameters.

Fuzzy control for vehicle status estimation considering roll stability and its application in target recognition of automobile cruise system

In order to resolve the goal confusion or missing on curve road, a target recognition method on automobile cruise system is put forward based on filtering and fuzzy control theory. A vehicle model ...

Research on the Intelligent Control and Simulation of Automobile Cruise System Based on Fuzzy System

In order to improve the active safety driving vehicle and alleviate the intension of driving fatigue, an intelligent control strategy of automobile cruise is put forward based on the throttle or braking pedal combined control adopting the fuzzy control theory. A fuzzy logic controller is presented, which consists of the two input variables, the deviation of the theoretical safe distance and relative distance and the relative velocity between the preceding vehicle and the cruise vehicle, and the single output variable, that is, the throttle opening or the braking pedal travel. Taking the test data of 1.6 L vehicle with auto-transmission as an example, the function on the intelligent cruise control system is simulated adopting MATLAB/Simulink aiming at different working conditions on the city road. The simulation results show that the control strategy possesses integrated capability of automated Stop & Go control, actively following the preceding vehicle on the conditions of keeping the safety distance and the constant velocity cruise. The research results can offer the theory and technology reference for setting dSPACE type and developing the integrated control product of automobile cruise system.

Direct-print/cure as a molded interconnect device (MID) process for fabrication of automobile cruise controllers

3D Molded interconnect device (MID) is referred to as a new paradigm of manufacturing electronic circuits with high design complexity by removing conventional wiring processes. Basically, manufacturing of MIDs consists of several steps: building a structure, creating conductive traces, and pick-and-place of electrical components. A 3D structure was built in a commercial Additive manufacturing (AM) machine, and conductive wires were created using a silver paste on the 3D structure with a predetermined design of an electronic circuit. A Direct-print/cure (DPC) process was developed to draw the conductive wires on the surface and simultaneously harden the created wires using thermal/radiation energy. This DPC system consists of a micro-dispensing device and light focusing module installed in a motorized xyz stage. Resistors were also printed using the developed DPC system and a synthesized carbon nanotube (CNT)/polymer composite. The CNT/polymer composite was characterized through a rheology test and Thermal gravimetric analysis (TGA). The resistance of the printed resistor can be controlled by varying its length and the width. Finally, an automobile cruise controller was fabricated with redesigned circuits for the suggested process and materials, which is a promising technology for building 3D MID parts.

차량 정속주행 시스템의 성능향상에 관한 연구 : 외란관측기 기법

The automobile cruise control system tries to maintain a constant velocity in the face of disturbance mainly caused by mass changes or changes in the slope of a road. The controller should compensate for such disturbances and model uncertainties. In this paper, we study on the disturbance observer based controller for cruise control system. In the presence of disturbances and model uncertainties, we carry out computer simulations in order to compare the performance of the conventional PI controller and DOB controller. From the simulation results, we found that the performance of DOB controller is superior to that of the conventional PI controller.

A Systematic Approach to Model Checking Human–Automation Interaction Using Task Analytic Models

Formal methods are typically used in the analysis of complex system components that can be described as “automated” (digital circuits, devices, protocols, and software). Human-automation interaction has been linked to system failure, where problems stem from human operators interacting with an automated system via its controls and information displays. As part of the process of designing and analyzing human-automation interaction, human factors engineers use task analytic models to capture the descriptive and normative human operator behavior. In order to support the integration of task analyses into the formal verification of larger system models, we have developed the enhanced operator function model (EOFM) as an Extensible Markup Language-based, platform- and analysis-independent language for describing task analytic models. We present the formal syntax and semantics of the EOFM and an automated process for translating an instantiated EOFM into the model checking language Symbolic Analysis Laboratory. We present an evaluation of the scalability of the translation algorithm. We then present an automobile cruise control example to illustrate how an instantiated EOFM can be integrated into a larger system model that includes environmental features and the human operator's mission. The system model is verified using model checking in order to analyze a potentially hazardous situation related to the human-automation interaction.

A cruise control for Parkinson's disease

As our knowledge of Parkinson's disease increases, we are developing sophisticated computational models of the neuronal networks that go awry in this condition. Such models can form a test bed for the rational design of control strategies to reduce the pathological dynamics. Although deep brain stimulation is becoming increasingly popular for treating Parkinson's disease, all of the present stimulation scenarios involve open-loop stimulation that does not take into account the brain's dynamics through feedback. Most engineering control systems, such as automobile cruise controls, make use of variants of proportional-integral-differential (PID) control strategies in response to a measured quantity. We here design an optimized PID controller for Parkinson's disease modulation. We adapted the sparse-structured model of a small network of synaptically coupled neurons in several basal ganglia areas, originally described by [4], to an efficient structured Matlab implementation. The major outputs from the basal ganglia are inhibitory signals from the globus pallidus interna (GPi) to its localized target areas within thalamus. Correspondingly, a natural view is that parkinsonian basal ganglia activity is transduced into motor symptoms through effects on thalamic dynamics. Specifically, computational [2] and data-based [1] analysis shows that pathological GPi synaptic outputs can compromise thalamic relay of excitatory signals, as can be assessed by calculation of a reliability index or by estimation of GPi output patterns. We assume an overarching principle for control in Parkinson's disease – we never want to put more than 1 multicontact electrode shaft in the brain. We start with GPi as a target, since the clinical differences between GPi and STN stimulation effects have not been well documented in controlled studies, and the GPi is a larger and easier target into which to insert stereotactic electrodes (see discussion in [3]). We set up 2 empirical control schemes: 1) a reliability control based upon the fraction of the sensorimotor spikes, accurately relayed 1-for-1 by the thalamic cells, and a GPi synaptic control based upon the estimated effective output of the GPi. We contrast several proportional control schemes based upon reliability: a frequency-proportional case, and a frequency-proportional-biased case. Although the energy expenditure is almost identical for both cases, the reliability is higher with adding a bias term. We contrast several proportional control schemes using a GPi output controller. Using an amplitude-proportional-derivative control scheme, where the error is equal to the instantaneous calculated GPi synaptic output minus the average GPi output. We flip the sign of the derivative term, from positive to negative, to explore whether amplifying or suppressing the instantaneous response to the differential error is best. Use of a negative differential coefficient yields substantially greater reliability and lower energy expenditure. Finally, we exhaustively optimize a PID controller using proportional, derivative, and integral terms, as shown in as shown in Figure ​Figure11. Figure 1 Thalamic reliability as a function of derivative, kd, and integral, ki, terms following exhaustive optimization. We have shown the feasibility of rational PID controller design for Parkinson's disease. Both reliability, and GPi synaptic outputs, can be estimated from reduced model based sensors, and the results of the PID scheme instituted in trials with real feedback controllers. Developing these reduced models for incorporation into future devices is the next step of this research.

Combining abductive reasoning and inductive learning to evolve requirements specifications

The development of requirements specifications inevitably involves modification and evolution. To support modification while preserving particular requirements goals and properties, the use of a cycle composed of two phases: analysis and revision is proposed. In the analysis phase, a desirable property of the system is checked against a partial specification. Should the property be violated, diagnostic information is provided. In the revision phase, the diagnostic information is used to help modify the specification in such a way that the new specification no longer violates the original property. An instance of the above analysis–revision cycle that combines new techniques of logical abduction and inductive learning to analyse and revise specifications, respectively is investigated. More specifically, given an (event-based) system description and a system property, abductive reasoning is applied in refutation mode to verify whether the description satisfies the property and, if it does not, identify diagnostic information in the form of a set of examples of property violation. These (counter) examples are then used to generate a corresponding set of examples of system behaviours that should be covered by the system description. Finally, such examples are used as training examples for inductive learning, changing the system description in order to resolve the property violation. This is accomplished with the use of the connectionist inductive learning and logic programming system—a hybrid system based on neural networks and the backpropagation learning algorithm. A case study of an automobile cruise control system illustrates the approach and provides some early validation of its capabilities.

External model and SyncCharts description of an automobile cruise control system

In this paper, a generic model is developed for smart instruments, and SyncCharts of the synchronous model are used to specify automated systems. The generic model provides an external description, which is the user's point of view, and the SyncCharts model gives a behavioral model of the system. From the complementary information offered by these two models of a device, a method to obtain a coherent SyncCharts from a part of the external model is proposed. The classical example of an automobile speed cruise control system is used for illustration.

Automatic generation of state invariants from requirements specifications

Automatic generation of state invariants, properties that hold in every reachable state of a state machine model, can be valuable in software development. Not only can such invariants be presented to system users for validation, in addition, they can be used as auxiliary assertions in proving other invariants. This paper describes an algorithm for the automatic generation of state invariants that, in contrast to most other such algorithms, which operate on programs, derives invariants from requirements specifications. Generating invariants from requirements specifications rather than programs has two advantages: 1) because requirements specifications, unlike programs, are at a high level of abstraction, generation of and analysis using such invariants is easier, and 2) using invariants to detect errors during the requirements phase is considerably more cost-effective than using invariants later in software development. To illustrate the algorithm, we use it to generate state invariants from requirements specifications of an automobile cruise control system and a simple control system for a nuclear plant. The invariants are derived from specifications expressed in the SCR (Software Cost Reduction) tabular notation.

Intelligent Device Formal Description Applied to Hybrid Systems

In this paper, the generic model, we have developped for smart instruments, is used to specify hybrid systems. The proposed model contains on one hand an external description which is the user’s point of view, and on the other hand, the internal description which provides the functionalities which have to be implemented. In particular, we focuse our interest on operating modes and we compare our description with other specifications of reactive systems such as Statecharts. The classical exemple of an automobile cruise control system is used for illustration.

A logic-model semantics for SCR software requirements

This paper presents a simple logic-model semantics for Software Cost Reduction (SCR) software requirements. Such a semantics enables model-checking of native SCR requirements and obviates the need to transform the requirements for analysis. The paper also proposes modal-logic abbreviations for expressing conditioned events in temporal-logic formulae. The Symbolic Model Verifier (SMV) is used to verify that an SCR requirements specification enforces desired global requirements, expressed as formulae in the enhanced logic. The properties of a small system (an automobile cruise control system) are verified, including an invariant property that could not be verified previously. The paper concludes with a discussion of how other requirements notations for conditioned-event-driven systems could be similarly checked.

Beyond objects

A standard demonstration problem in object-oriented programming is the design of an automobile cruise control. This design exercise demonstrates object-oriented techniques well, but it does not ask whether the object-oriented paradigm is the best one for the task. Here we examine the alternative view that cruise control is essentially a control problem. We present a new software organization paradigm motivated by process control loops. The control view leads us to an architecture that is dominated by analysis of a classical feedback loop rather than by the identification of discrete stateful components to treat as objects. The change in architectural model calls attention to important questions about the cruise control task that aren't addressed in an object-oriented design.

State-based model checking of event-driven system requirements

It is demonstrated how model checking can be used to verify safety properties for event-driven systems. SCR tabular requirements describe required system behavior in a format that is intuitive, easy to read, and scalable to large systems (e.g. the software requirements for the A-7 military aircraft). Model checking of temporal logics has been established as a sound technique for verifying properties of hardware systems. An automated technique for formalizing the semiformal SCR requirements and for transforming the resultant formal specification onto a finite structure that a model checker can analyze has been developed. This technique was effective in uncovering violations of system invariants in both an automobile cruise control system and a water-level monitoring system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

State-based model checking of event-driven system requirements

In this paper, we demonstrate how model checking can be used to verify safety properties for event-driven systems. SCR tabular requirements describe required system behavior in a format that is intuitive, easy to read, and scalable to large systems (e.g., the software requirements for the A7 aircraft). Model checking of temporal logics has been established as a sound technique for verifying properties of hardware systems. We have developed an automated technique for formalizing the semiformal SCR requirements and for transforming the resultant formal specification onto a finite structure that a model checker can analyze. This technique was effective in uncovering violations of system invariants in both an automobile cruise control system and a water-level monitoring system.