Due to its importance in security, syntax analysis has found usage in many high-level programming languages. The Lisp language has its share of operations for evaluating regular expressions, but native parsing of Lisp code in this way is unsupported. Matching on lists requires a significantly more complicated model, with a different programmatic approach than that of string matching. This work presents a new automata-based approach centered on a set of functions and macros for identifying sequences of Lisp S-expressions using finite tree automata. The objective is to test that a given list is an element of a given tree language. We use a macro that takes a grammar and generates a function that reads off the leaves of a tree and tries to parse them as a string in a context-free language. The experimental results indicate that this approach is a viable tool for parsing Lisp lists and expressions in the abstract interpretation framework

In this study, “homeostasis”, the function by which living things keep their constancy, was emulated as a lighting control for a building space. The algorithm we developed mimics the mechanisms of the endocrine and immune systems. The endocrine system transmits information entirely, whereas the immune system transmits information with a concentration gradient. A lighting control system using the proposed algorithm was evaluated in a simulation and experiment using a sensor agent robot. In this algorithm, a robot recognizes a person’s behavior and uses it to decide his or her preference as to the illuminance. The results indicate that the algorithm can be used to realize a comfortable lighting control in several situations.

The mathematical model of hydraulic drive unit of quadruped robot was built in this paper. According to the coupling characteristics between position control system and force control system, the decoupling control strategy was realized based on diagonal matrix method in AMESim?. The results of simulation show that using diagonal matrix method can achieve the decoupling control effectively and it can achieve the decoupling control more effectively with the method of not offset pole-zero in the S coordinate. This research can provide theoretical basis for the application of test system of hydraulic drive unit.

The steam turbine control system is strongly non-linear in all operating conditions. Proportional-Integral-Derivative (PID) controller that is currently used in control systems of many types of equipment is not considered highly precision for turbine speed control system. A fine tuning of the PID controller by some optimization technique is a desired objective to maintain the precise speed of the turbine in a wide range of operating conditions. This Paper evaluates the feasibility of the use of Particle Swarm Optimization (PSO) method for determining the optimal Proportional-Integral-Derivative (PID) controller parameters for steam turbine control. The turbine speed control is modelled in SimulinkTM with PID controller and the PSO algorithm is implemented in MATLAB to optimize the PID function. The PSO optimization technique is also compared with Genetic Algorithm (GA) and it is validated that PSO based controller is more efficient in reducing the steady-states error; settling time, rise time, and overshoot limit in speed control of the steam turbine control.

We consider and we study a general concept of domination for controlled and observed distributed systems. We give characterization results and the main properties of this notion for controlled systems, with respect to an output operator. We also examine the case of actuators and sensors. Various other situations are considered and applications are given. Then, we extend this study by comparing observed systems with respect to a control operator. Finally, we study the relationship between the notion of domination and the compensation one, in the exact and weak cases.

A novel constant force feedback mechanism based on fuzzy logic for tapping mode Atomic Force Microscopes (AFM) is proposed in this paper. A mathematical model for characterizing the cantilever-sample interaction subsystem which is nonlinear and contains large uncertainty is first developed. Then, a PID-like fuzzy controller, combing a PD-like fuzzy controller and a PI controller, is designed to regulate the controller efforts and schedule the applied voltage of the Z-axis of the piezoelectric tube scanner to maintain a constant tip-sample interaction force during sample-scanning. Using the PID-like fuzzy controller allows the cantilever tip to track sample surface rapidly and accurately even though the topography of the surface is arbitrary and not given in advance. This rapid tracking response facilitates us to observe samples with high aspect ratio micro structures accurately and quickly. Besides, the overshoot which will result in tip crash in commercial AFMs with a traditional PID controller could be avoided. Additionally, the controller efforts can be intelligently scheduled by using the fuzzy logic. Thus, continuous manual gain-tuning by trial and error such as those in commercial AFMs is alleviated. In final, computer simulations and experimental verifications are provided to demonstrate the effectiveness and confirm the validity of the proposed controller.

The diagnoses in industrial systems represent an important economic objective in process industrial automation area. To guarantee the safety and the continuity in production exploitation and to record the useful events with the feedback experience for the curative maintenance. We propose in this work to examine and illustrate the application ability of the spectral analysis approach, in the area of fault detection and isolation industrial systems. In this work, we use a combined analysis diagram of time-frequency, in order to make this approach exploitable in the proposed supervision strategy with decision making module. The obtained results, show clearly how to guarantee a reliable and sure exploitation in industrial system, thus allowing better performances at the time of its exploitation on the supervision strategy.

This paper presents a slip suppression controller using sliding mode control method for electric vehicles which aims to improve the control performance and the energy conservation by controlling the slip ratio of wheel. In this method, a robust sliding mode controller against the model uncertainties is designed to obtain the maximum driving force by suppressing the slip ratio. The numerical simulations for one wheel model under variations in mass of vehicle and road condition are performed and demonstrated to show the effectiveness of the proposed method.

A novel speed control design of 4WD electric vehicle (EV) to improve the comportment and stability under different road constraints condition is presented in this paper. The control circuit using intelligent adaptive fuzzy PI controller is proposed. Parameters which guide the functioning of PI controller are dynamically adjusted with the assistance of fuzzy control. The 4WD is powered by four motors of 15 kilowatts each one, delivering a 384 N.m total torque. Its high torque (338 N.m) is instantly available to ensure responsive acceleration performance in built-up areas. The electric drive canister of tow directing wheels and tow rear propulsion wheels equipped with tow induction motors thanks to their light weight simplicity and their height performance. Acceleration and steering are ensure by electronic differential, the latter control separately deriving wheels to turn at any curve. Electric vehicle are submitted different constraint of road using direct torque control. Electric vehicle are simulated in MATLAB SIMULINK. The simulation results have proved that the intelligent fuzzy PI control method decreases the transient oscillations and assure efficiency comportment in all topologies road constraints, straight, curved road, descent.

Internet-based teleoperation employs robots and internet a two breakthrough technologies to manipulate robots from distance for different applications. Variable and unknown time delay dynamics of internet is the main obstacle for realtime teleoperation via internet. In this paper the internet delay dynamics and its characteristics have been studied based on the measurement in different nodes. Then a black-box model for end-to-end internet delay dynamics has been developed using system identification and Auto-Regressive eXogeneous (ARX) model. Our experimental studies show a regular periodic behaviour in long-term intervals of internet delay variation and also confirm the accuracy and reliability of our theoretical and modelling derivations. This paper also introduces a novel multivariable control method for real-time telerobotic operations via Internet. Random communications delay of the Internet can cause instability in realtime closed-loop telerobotic systems. When a single identification model is used, it will have to adapt itself to the operating condition before an appropriate control mechanism can be applied. Slow adaptation may result in a large transient error. As an alternative, we propose to use a Multiple Model framework. The control strategy is to determine the best model for the current operating condition and activate the corresponding controller. We propose the use of Multi-Model Adaptive Control Theory and Multivariable Wave prediction method to capture the concurrency and complexity of Internet-based teleoperation. The results confirm the efficiency of the proposed technique in dealing with constant and variable delay dynamics of internet.