Stability analysis and control method of a variable structure detection robot for underground rescue

Purpose. The purpose of the article is to develop a methodology for creating cone crusher adaptive control system based on the model-based design method for automated software generation of microprocessor controllers. Methodology. A method based on a block-oriented predictive model was used to generate control signals for the cone crusher. The parameters and structure of this model were identified in real time using measured data from the plant. A prototype of the control system was created in MATLAB/Simulink. Then, the model-based design method was used to generate software for digital signal processors. Mathematical statistics methods were employed to analyze the experimental results. Findings. A method of model-based design of an adaptive control system for a cone crusher has been developed. This system uses a predictive model of a block-oriented structure. This model adjusts the predictive controller’s structure and parameters directly during operation. This approach makes it possible to divide the functions of identifying the process model and generating controls between the two digital controllers. Consequently, the average computational time is reduced while ensuring the stabilization of the degree of homogeneity of ore crushing and separate output of the control size class, with respective standard deviation coefficients not exceeding 3.42 and 1.83 %, respectively. Originality. The regularity of the effect of the closed-side setting and the eccentric speed on the particle size distribution of crushed ore has been established. This shows that high homogeneity of the crushed product is ensured by simultaneously adjusting these input coordinates. We propose a new method for synthesizing an adaptive cone crusher control system based on a model-based design approach. This method provides automated real-time generation of software for microprocessor-based controllers, allowing the system to quickly adjust to changes in rock mass characteristics and other disturbances. Practical value. A hardware and software implementation of an adaptive control system for a cone crusher is proposed. This system is based on a block-oriented predictive model. The model ensures the stabilization of the required ore particle size distribution. This stabilization is achieved by adjusting the closed-side setting and the eccentric speed. The system is based on 16-bit, low-cost digital signal processors. A prototype of the system was tested in a crushing plant at a metallurgical enterprise.

Adaptive traffic control systems continuously monitor traffic conditions on an arterial and adjust traffic signal timings to accommodate variation in traffic volume and minimize stops and delays. This paper describes currently practical adaptive control systems which have been used in the United States and worldwide, which include Adaptive Control System-Lite (ACS-Lite), Optimization Policies for Adaptive Control (OPAC), Real-Time Hierarchical Optimized Distributed and Effective System (RHODES), Sydney Coordinated Adaptive Traffic System (SCATS) and Split Cycle Offset Optimization (SCOOT). The comparisons of the benefits from past experiences, cost and hardware requirements will help the traffic engineers and decision makers a guideline to select the optimized adaptive control system based on research objectives.

SummaryIn this study, we present a reinforcement learning (RL)‐based flight control system design method to improve the transient response performance of a closed‐loop reference model (CRM) adaptive control system. The methodology, known as RL‐CRM, relies on the generation of a dynamic adaption strategy by implementing RL on the variable factor in the feedback path gain matrix of the reference model. An actor‐critic RL agent is designed using the performance‐driven reward functions and tracking error observations from the environment. In the training phase, a deep deterministic policy gradient algorithm is utilized to learn the time‐varying adaptation strategy of the design parameter in the reference model feedback gain matrix. The proposed control structure provides the possibility to learn numerous adaptation strategies across a wide range of flight and vehicle conditions instead of being driven by high‐fidelity simulators or flight testing and real flight operations. The performance of the proposed system was evaluated on an identified and verified mathematical model of an agile quadrotor platform. Monte‐Carlo simulations and worst case analysis were also performed over a benchmark helicopter example model. In comparison to the classical model reference adaptive control and CRM‐adaptive control system designs, the proposed RL‐CRM adaptive flight control system design improves the transient response performance on all associated metrics and provides the capability to operate over a wide range of parametric uncertainties.

Nowadays, control systems for stepper motors are well defined by using microcontrollers. The stepper motors are very good in positioning tasks and measurement tasks. Now there are some FPGA based developments for stepper motor controlling systems because of the complexity of the controlling system. But the new FPGA systems don't use the whole functionality and benefits of the FPGAs like the parallelism of computing tasks or the right structured Hardware-, Software-Co-Design. In this paper we want to show, that there are many possibilities to use the FPGA benefits for the development of stepper motor control systems and we show also an outlook to new developments and systems. Like an adaptive control system, which controls the parameters of the stepper motor and inspects them for aging.

In glutamate fermentation, intermittent feeding is the most widely used glucose feed strategy. This feeding strategy causes severe fluctuations of glucose concentration and osmotic pressure in fermentation broth, which deteriorates the viability of the cell and reduces glutamate production in turn. In order to maintain glucose concentration at stable and constant levels, an on-line prediction and feedback control system based an empiric mass balance model was developed. However, the control system did not work properly and sometimes glucose concentration could even decline to 0 level (glucose exhaustion), as the model parameter varies in different runs. As a result, a novel model-based adaptive feedback control system incoporating with an artificial neural network (ANN) based pattern reconition unit for on-line diagnosizing the fault of glucose exhaustion was proposed and applied for glutamate fermentation. This adaptive control system could accurately detect glucose exhaustion when it occurs, and then immediately updates the control parameter based on some pre-defined rule. With the proposed control system, glucose was automatically fed, and its concentration could be maintained at desired levels constantly. As a result, glutamate concentration was 17 ~ 30% higher than that of the traditional fermentations using the intermittent glucose feed strategy.

Inertial stabilization systems are designed to maintain the angular orientation of an optical system or other device in inertial space. Applications include surveillance, target tracking, flight control, weapon pointing, navigation, communication and others. Typically, some variation of a closed loop control system is employed which uses feedback from a gyro. The object of this paper is to consider the potential benefits and some approaches to adaptive control algorithms. Ideally, an adaptive control system would adjust itself to achieve "optimal performance" with respect to some criteria in the presence of changing plant characteristics, changing noise characteristics and a changing disturbance environment. Potentially, such a design could provide robust control for a variety of system configurations, mission conditions and applications resulting in significant reductions in both development and production costs as well as improved performance. First, the general stabilization problem and some conventional control system designs are briefly reviewed. Then a variety of adaptive techniques are surveyed. Finally, the current status and results of a joint research project between Texas Instruments and the University of Texas at Arlington whose goal is to develop an adaptive stabilization control system is discussed.

Nowadays actual scientific problem of renewable energy is the problem of developing control systems, that ensure the generation of stable voltage in a changing environment. This paper presents a structure and methods of synthesis of control system development, which allow to decide the indicated problem. An electric subsystem of wind power plant is a well-known structure with well-known advantages, consisting mainly of double-fed induction generator (DFIG) and power converter in the circuit of rotor. Operation of the control system based on the original nonlinear mathematical model of DFIG in rotational dq coordinates, taking into account the nonlinear external and internal DFIG disturbances, such as inductances of coil winding, changes of coil winding resistances from temperature, etc. The study received mathematical model, adaptive control algorithms and its computer simulation of the wind turbine with DFIG. Introduction An increasing requirement in energy resources at unstable oil prices stimulate to search the alternative decisions of power problems. One of the most successfully developed types of alternative energy is wind power. Its rapid growth observed in the world, proofing an attractiveness of this technology. It is expressed in the purity, reliability and input speed. So, according to Global Wind Energy Council (GWEC), to the end of 2015 global wind power capacity will reach 609 GW, compared to 237. 4 gigawatts at the end of 2011. The three leading world markets remain the China, U. S. and Europe. In recent years, the rapid growth of installed wind power capacity turned out to be possible through the development and implementation of new technological solutions, one of which is DFIG used as generator in wind power plants(WPP). Such DFIG are widely used in powerful WPP, as they allow to convert the available wind energy more efficiently, especially in periods of weak winds. It is known that the parameters of the generated voltage depends on terms of environment. At the same time, the necessity of quality stable voltage generation sets the problem of technological decisions development, allowing to minimize influence of different factors on output voltage quality. Such a technological solution is adaptive control system (CS) of a WPP with DFIG , permitting high speed reaction to wind speed changes and the rate of the connected electrical load, thus maintaining the stability of the generator output voltage. Synthesizing an adaptive high-speed CS and using the structure of WPP with DFIG it becomes possible to design and build these types of wind turbines. Synthesis of nonlinear CS Nonlinear CS control law. The solution of the indicated problem, offered in this paper, is based on the nonlinear model of DFIG in rotational dq coordinates, as in the conditions of different disturbances, linearizing appears uneffective [1]. Because, coming from the structure of WPP, control circuit is a rotor circuit, then primary control objective is feed on it control voltage of some parameters, at that DFIG output voltage remains unchanging and corresponds to set, without depending on influences. As it applies to a model, it is necessary to get the control values of voltages International Conference on Advances in Energy, Environment and Chemical Engineering (AEECE-2015) © 2015. The authors Published by Atlantis Press 1 on the dq rotor axes dr V and qr V , at the well-known required stator voltages ref ds V and ref qs V . The classic mathematical model of DFIG does not take into account the nonlinear changes of its parameters, such as winding inductances, changes of winding resistances from temperatures etc., accepting their permanent, that is not quite right. Meantime, in real DFIG such changes have an influence on control quality, so the synthesis of control system, which is taking into account such nonlinear disturbances, is an actual task. The disturbances arising up from nonlinear character of the control object are difficult to mathematical description, however valuation of these disturbances with the subsequent bringing of adjustments in work of CS on the basis of such estimation is a fully solvable task. For this purpose, in the standard mathematical model of DFIG we will add some functions of immeasurable disturbances, and (Eq.1), accordingly for the stator d and q axes currents, and next we synthesize control laws.

This paper presents an adaptive learning control system for the F-8 DFBW aircraft. The purpose of the control system is to learn plant parameter curves that affect the flight of the aircraft. These parameter curves are used to adjust the gain schedule of the aircraft in a prescribed manner to account for changing aircraft characteristics. The learning control system is an adjustable blend of a gain scheduling system and an adaptive control system in the sense that it takes the best of these two systems and eliminates the undesirable features of each.

An adaptive control system with good following characteristics is designed for the electro-hydraulic servo system which are strongly coupled and seriously nonlinear. The model of position servo system on air rudder is discussed with the uncertain system equivalent to the one with parametric variable double input and single output to establish a Popov-MRAC (Model Reference Adaptive Control) system. The simulation results show that the Popov MRAC system has good following characteristics, precision and robustness.

The performance of a damping-controllable dynamic damper was investigated with an adaptive neural net control system. The damping controllability of the dynamic damper was accomplished by introducing the Electro-Rheological (ER) fluid, which is known as one of the highly functional materials and whose apparent viscosity can be varied in accordance with applied electric field strength in a wide range as well as in a short time. As a control system for the present dynamic damper, an adaptive neural net control system was developed ; it was composed of a forward model network and a controller network. With the proposed neural net control system, the damping-controllable dynamic damper can be tuned by itself even if response of a structure shows nonlinearity to input disturbances or varies its own dynamic characteristic. Moreover, the vibration amplitude corresponding to several natural frequencies can be reduced with only a single dynamic damper. Numerical and experimental investigations were performed, and the results shows the superiority of the present adaptive vibration control system.

This paper investigates the problem of yaw moment control of humanoid robot and presents a robust adaptive control system for compensating the undesired yaw moment. In order to get the ideal ankle joint trajectory with low energy consumption, a novel yaw moment control based on ankle is proposed. The main strategy in this method is to adjust ankle joint trajectory in a way to exert a moment for counteracting the factors which generate the undesired yaw moment. Given the optimized ankle joint angles motion, an adaptive fuzzy control system is proposed to track the desired trajectories with model uncertainties and the stability proof is provided. Simulation results validate the proposed method.

The trend in future space high precision reflectors is going towards large aperture, lightweight and actively controlled deformable antennas. An adaptive shape control system for a Carbon Fiber Reinforced Composite (CFRC) reflector is conducted by Piezoelectric Ceramic Transducer (PZT) actuators. This adaptive shape control system has been shown to effectively mitigate common low order wave-front error, but it is inevitably plagued by high order wave-front error control. In order to improve the controllability of the adaptive CFRC reflector control system for high order wave-front error, the design of adaptive CFRC reflector requires optimizing further. According to numerical and experimental results, the print-through error induced by manufacturing and PZT actuators actuation is a type of predominant high order wave-front error. This paper describes a design which some secondary rib elements are embedded within the triangular cells of the primary ribs. These small secondary ribs are designed to support the reflector surface’s weak region. Controllability of this new adaptive CFRC reflector control system with small secondary ribs is evaluated by generalized Zernike functions. This new design scheme can reduce high order residual error and suppress the high order wave-front error such as print-through error. Finally, design parameters of the adaptive CFRC reflector control system with small secondary ribs, such as primary rib height, secondary rib height, cut-out height of primary rib, are optimized.

The paper presents a curving adaptive cruise control (ACC) system that is coordinated with a direct yaw-moment control (DYC) system and gives consideration to both longitudinal car-following capability and lateral stability on curved roads. A model including vehicle longitudinal and lateral dynamics is built first, which is as discrete as the predictive model of the system controller. Then, a cost function is determined to reflect the contradictions between vehicle longitudinal and lateral dynamics. Meanwhile, some I/O constraints are formulated with a driver permissible longitudinal car-following range and the road adhesion condition. After that, desired longitudinal acceleration and desired yaw moment are obtained by a linear matrix inequality based robust constrained state feedback method. Finally, driver-in-the-loop tests on a driving simulator are conducted and the results show that the developed control system provides significant benefits in weakening the impact of DYC on ACC longitudinal car-following capability while also improving lateral stability.

A New Approach to the Design of an Adaptive Control System

This paper presents a new control law based on type-2 fuzzy logic system (T2FLS) for the Cessna Citation X aircraft during cruise. This methodology combines three control systems: a T2FLS, a sliding mode control (SMC) system, and an adaptive control system. Differing from conventional controllers, this control system can deal with uncertainties and aircraft dynamics variations using the T2FLS approximator. The approximated functions were updated during the simulation iterations using adaptation laws derived from the Lyapunov theorem. The adaptability characteristic of this controller allows updating the approximated functions while the other design parameters remain unchanged. This fact simplifies the controller design process and eliminates the need to use a group of conventional controllers with different gains to control the aircraft in various flight conditions. In addition, the sliding mode control system helps to guarantee the aircraft’s stability and robustness, along with two other methodologies in the presence and absence of turbulence. The performance of this control methodology was validated with a nonlinear simulation platform developed for the Cessna Citation X business aircraft using accurate flight data derived from a Level D flight simulator at the Research Laboratory in Active Controls, Avionics and AeroServoElasticity (LARCASE).