Modern Control Approaches Research Articles

A Review on Predictive Control Technology for Switched Reluctance Motor System

The significance of employing control strategies on a switched reluctance motor (SRM) is that they can reduce vibration noise and torque ripple. With the rapid development of digital system processors, predictive control (PC), as a modern control approach, is increasingly applied to enhance the dynamic performance and operational efficiency of SRMs. This review provides a comprehensive overview of the current state of research on PC strategies of SRMs and classifies PC technologies, such as generalized predictive control (GPC), hysteresis predictive control (HPC), deadbeat predictive control (DPC), and model predictive control (MPC). It summarizes the PC schemes from the aspects of predictive current control (PCC), predictive torque control (PTC), and other PC, and it discusses the current trends in technology development, as well as potential research directions. The insights presented herein aim to facilitate further investigations into predictive control techniques for SRM.

Multi-Rate Data Fusion for State and Parameter Estimation in (Bio-)Chemical Process Engineering

For efficient operation, modern control approaches for biochemical process engineering require information on the states of the process such as temperature, humidity or chemical composition. Those measurement are gathered from a set of sensors which differ with respect to sampling rates and measurement quality. Furthermore, for biochemical processes in particular, analysis of physical samples is necessary, e.g., to infer cellular composition resulting in delayed information. As an alternative for the use of this delayed measurement for control, so-called soft-sensor approaches can be used to fuse delayed multirate measurements with the help of a mathematical process model and provide information on the current state of the process. In this manuscript we present a complete methodology based on cascaded unscented Kalman filters for state estimation from delayed and multi-rate measurements. The approach is demonstrated for two examples, an exothermic chemical reactor and a recently developed model for biopolymer production. The results indicate that the the current state of the systems can be accurately reconstructed and therefore represent a promising tool for further application in advanced model-based control not only of the considered processes but also of related processes.

Operational Efficiency Improvement of PEM Fuel Cell—A Sliding Mode Based Modern Control Approach

The efficiency and durability of a Proton Exchange Membrane Fuel Cell (PEMFC) can be improved with proper controller design to regulate the flow of reactants, cell stack temperature and humidity of the membrane. In this paper, sliding mode controllers (SMC) are proposed for a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">polymer electrolyte membrane fuel cell</i> PEMFC. In particular, first order SMC and second order SMC based on super twisting algorithm are designed and investigated. The actual process has been formulated in simulation by Pukurushpan’s ninth order model. Performance of both control laws has been compared in simulation in MATLAB/Simulink environment in terms of oxygen excess ratio, net power generated, stack voltage/power produced and compressor motor voltage. Simulation results dictate that second order SMC demonstrates superior performance in terms of set-point tracking and disturbance rejection. The designed controller makes the interaction of various subsystems in a smooth manner and consequently improves the overall efficiency of the system and prolongs the stack life of the fuel cells.

Stabilization and Optimization of Design Parameters for Control of Inverted Pendulum

In this work, we study the dynamic response of the most popular unstable control problem, the inverted pendulum in terms of classical control theory. The theoretical and experimental results presented here explore the relationship between changes in the indirect tuning parameters from the linear quadratic regulator (LQR) design, and the final system performance effected using the feedback gains specified as the LQR weight constraints are changed. First, we review the development of the modern control approach using full state-feedback for stabilization and regulation, and present simulation and experimental comparisons as we change the optimization targets for the overall system and as we change one important system parameter, the length of the pendulum. Second, we explore the trends in the response by developing the generalized root locus for the system using incremental changes in the LQR weights. Next, we present a family of curves showing the local root locus and develop relationships between the weight changes and the system performance. We describe how these locus trends provide insight that is useful to the control designer during the effort to optimize the system performance. Finally, we use our general results to design an effective feedback controller for a new system with a longer pendulum and present experiment results that demonstrate the effectiveness of our analysis.

A robust two-stage active disturbance rejection control for the stabilization of a riderless bicycle

In this work we propose a two-stage observer-based feedback control approach to automatically stabilizing a riderless bicycle in its upright position when moving forward at a constant speed. Our strategy uses a modern control approach called Active Disturbance Rejection Control (ADRC), based on Generalized Proportional Integral (GPI) extended observers, to estimate a unified signal that groups all the discrepancies between an adopted linear model and the actual behavior of the plant. These estimations are used in the feedback controller as an additive, close cancellation and terms devising proper output feedback control laws that linearly regulate the lean angle with respect to its upright position. From a control-design perspective, the bicycle is a perturbed, uncertain system with an unstable and non-linear behavior that is strongly forward speed dependent. The ADRC scheme allows one to solve this problem easily by using a control strategy based on an acceptable mathematical model derived from lumped-parameter analysis, and its effectiveness has been validated by the successful results from real implementation experiments on an instrumented bicycle prototype. A detailed description of all the stages of the mechatronics process design is included for a proper reference.

Guest Editorial

Guest Editorial

Managing storage pests of maize: Farmers' knowledge, perceptions and practices in western Kenya

Insect pests are a key constraint to effective utilization of cereal crops in sub-Saharan Africa (SSA), with damage caused by these pests in the stores of particular concern. Although a number of approaches have been advanced for control of storage pests of maize, uptake remains a challenge, with effectiveness of some approaches being questionable. We conducted a survey in western Kenya among 330 respondents using face to face interviews and focus group discussions to evaluate farmers' practices, knowledge and perceptions of storage pests of maize, and their current practices in managing such pests as a basis for development of efficient integrated pest management (IPM) approaches for the pests. Majority of the respondents stored maize in traditional granaries, with less than 10% of them using modern improved facilities, mainly due to inability to afford these. Majority of the respondents also cited attack of their stored grains by a number of insect pests, causing about 40% grain losses. The larger grain borer, Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae), sawtoothed grain beetle, Oryzaephilus surinamensis (L) (Coleoptera: Silvanidae), and maize weevil, Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae), were perceived as the most common and damaging pests. Farmers' perceptions of pests were positively and significantly influenced by level of education and farming experience, indicating that education and experience build farmers' understanding of storage pests. Storing maize in unshelled form seemed to result in less pest attack, although majority of the respondents stored their maize in shelled form. Moreover, local maize varieties were perceived to be resistant to pests. The farmers applied various control methods, with sun-drying being the most popular practice. Usage of pesticides was minimal, mainly due to high costs, lack of information, and unavailability of appropriate and effective products. There were also other cultural methods applied, such as use of smoke and insecticidal plants. The respondents decried lack of training and extension services on storage pests and their management, underscoring the need to develop extension services. The underlying mechanisms of the perceived pest resistance in local varieties of maize and cultural pest management methods need to be established for exploitation in development of effective IPM approaches. There is also need to address the challenges hindering uptake of modern storage and control approaches.

Distributed MPC for Upstream Oil & Gas Fields - a practical view

This work aims to improve corporate functional departments’ confidence in adopting modern control approaches in new scenarios and thus presents control structure solutions based on MPC for two control problems facing existing upstream oil & gas production plants; these are the disturbance growth in the series connected process and the control system dependency on operators. The proposed approach integrates distributed MPC (DMPC) as a master controller for the existing classical control of each subsystem, with a focus on those with high interaction phenomena. The proposed DMPC also considers safeguarding, constraints and the enhancement of plant-wide optimal performance. The suggested control solution reduces the role of control room operators which is shown to reduce the growth in the impact of process disturbances. Compared with some alternative control structures (centralised MPC, decentralised MPC, distributed MPC (DMPC), and hierarchical DMPC) this proposal is simple, inexpensive to implement, and critically, builds on the local team operational experience and maintenance skills.

RIDE AND HANDLING ANALYSIS FOR AN ACTIVE ANTI-ROLL BAR: CASE STUDY ON COMPOSITE NONLINEAR CONTROL STRATEGY

This paper presents a comparison of ride and handling analysis for an active anti-roll bar system using various types of controller. Work using conventional and modern control approaches has been investigated by previous researches. This study further extends this work by investigating a particular modern control technique using a linear quadratic regulator, linear quadratic Gaussian and composite nonlinear feedback controller in designing the closed loop feedback for an anti-roll bar system control scheme. A simple linear quadratic regulator and a linear quadratic Gaussian are first investigated. An active anti-roll bar system has to balance the trade-off between ride comfort and handling performance. The new linear quadratic Gaussian composite nonlinear feedback (LQG-CNF) fusion control strategy is developed to improve the performances on vehicle ride comfort and handling for an active anti-roll bar system. The linear half car model is combined with a single track model with roll dynamics. The performance of the controllers is compared and the simulation results show that the proposed control strategy gives better performance in terms of vehicle ride comfort and handling.

Short Review on Controller Design Approaches of Heating Ventilation Air Conditioner Systems Towards Energy-Efficient Buildings

The paper gives an overview of heating, ventilation and air-conditioning (HVAC) system and controller design approaches towards energy-efficient. The controller design approaches for the HVAC system can be categorized into the 3 main classes, which are the classical control approach, modern control approach and artificial intelligence control approach. Each category consists of different type of controllers which are presented. In classical controller approaches ‘ON’ and ‘OFF’ or PID controllers are the most significant influence to control the HVAC system whereas the modern control approach is used to reduce the weakness of the classical control approach. The artificial control approach is used to multi-criteria objectives of thermal comfort and energy saving without any need to mathematically model the system. The characteristics, as well as the advantage and limitation for each strategy are presented

Decentralised control for complex systems - an invited survey

With the advancement of science and technology, practical systems are becoming more complex. Decentralised control has been recognised as a practical, feasible and powerful tool for application to large scale interconnected systems. In this paper, past and recent results relating to decentralised control of complex large scale interconnected systems are reviewed. Decentralised control based on modern control approaches such as variable structure techniques, adaptive control and backstepping approaches are discussed. It is well known that system structure can be employed to reduce conservatism in the control design and decentralised control for interconnected systems with similar and symmetric structure is explored. Decentralised control of singular large scale systems is also reviewed in this paper.

Design and Development of a Class of Rotorcraft-Based UAV

We discuss the development of a mini- quadrotor system and coaxial quadrotor system for indoor and outdoor applications. The attitude control system consists of a stability augmentation system and a modern control approach. To perform an experimental flight test, a PID controller is used to validate our aerodynamic modelling and basic electronics hardware is developed in a simple configuration. We use a low-cost 100 Hz AHRS for inertial sensing, infrared (IR) sensors for horizontal ranging, an ultrasonic sensor for ground ranging and an AVR microcontroller for the flight control computer. A ground control system is developed for the monitoring and gathering of flight data. Based on the modelling and simulation data of the mini-quadrotor system, a flight test is performed and automatic hovering ability is implemented. A collision detection system is one of the important parts of an indoor and outdoor flight test. To overcome the payload limitation of the mini- quadrotor system, we design a coaxial quadrotor system and we use a Kinect sensor as the collision detect sensor. Kinect sensors give 3D depth information and the collision detection system uses that information.

3G3 集中系モデルを用いた現代制御理論に基づく能動騒音制御(&lt;OS5&gt;振動・音響の計測,解析および制御3)

3G3 集中系モデルを用いた現代制御理論に基づく能動騒音制御(&lt;OS5&gt;振動・音響の計測,解析および制御3)

Design of an Autonomous Hover Control System for a Small Quadrotor

This paper discusses the development of the control system of a mini quadrotor in Konkuk University for indoor applications. The attitude control system consists of a stability augmentation system, which acts as the inner loop control, and a modern control approach based on modeling will be implemented as the outer loop. The inner loop control was experimentally satisfied by a proportional-derivative controller; this was used to support the flight test in order to validate the modeling. This paper introduces the mathematical model for the simulation and design of the optimal control on the outer loop control. To perform the experimental tests, basic electronic hardware was developed using simple configurations; a microcontroller used as the embedded controller, a low-cost 100 Hz inertial sensors used for the inertial sensing, infra-red sensors were employed for horizontal ranging, an ultrasonic sensor was used for ground ranging and a high performance propeller system built on an quadrotor airframe was also employed. The results acquired from this compilation of hardware produced an automatic hovering ability of the system with ground control system support for the monitoring and fail-safe system.

LQG WITH FUZZY CORRECTION MECHANISM IN TILTING RAILWAY VEHICLE CONTROL DESIGN.

This paper present work on modern control approaches in titling railway vehicles. The design of the Linear Quadratic Gaussian with integral action controller provides the required tilt compensation, while the addition of the fuzzy mechanism to the controller improves the system performance both for the deterministic and stochastic track. Moreover, the use of multiobjective GA as a tuning method seeks an optimum value based on the imposed constraints in the objective functions.

Adaptation, modelling of dynamic drives and controller design in servomechanism pneumatic systems

Problems associated with the application of modern control approaches to industrial servomechanism systems, developed using pneumatic techniques, are presented and discussed. Two major tasks for servosystems are investigated: point-to-point and trajectory-tracking control. Presentations of the drive system, based on fundamental phenomenology equations and statistically identified models, are introduced and discussed. This knowledge combined with identified roles for drives leads to approaches that can be useful in the design of appropriate controller algorithms for ‘high-tech’ servosystems. Their variety, including state–space control, fast adaptation control, predictive control and multipurpose (movement and force) control is presented. Application of these techniques in industrial conditions involves different technical problems, e.g. measurability of signals, time limit on control values or sensitivity to variations of load, working regime and supply conditions. Proposals on how to cope with these problems are described. Extended testing under industrial conditions is described briefly.

A transformer resonant phase‐shifted PWM DC–DC converter for X‐ray power generator and its fuzzy logic‐based learning control scheme

AbstractIn general, medical‐use high‐voltage X‐ray power generators are operated at a variety of required output DC voltages and output current settings for the X‐ray tube. A phase‐shifted PWM inverter‐fed DC–DC power converter with a high‐voltage transformer parasitic resonant link which is used for an X‐ray power generator inherently has stiff nonlinear characteristics due to phase‐shifted voltage regulation and diode cutoff operation in a high‐voltage rectifier because of the wide load setting ranges in practical applications. However, the superior output voltage response required for a medical‐use X‐ray power generator could not be sufficiently implemented by various modern linear control approaches because a precise mathematical description with dynamic modeling could not be formulated for wide load variations. For controlling such a nonlinear DC–DC power conversion system, a fuzzy reasoning‐based learning control technique that duplicates human capabilities and much experience in understanding the dynamic and static behavior of the system are more suitable and effective. This paper presents a phase‐shifted PWM full bridge inverter‐type high‐voltage DC–DC power converter with a high‐voltage transformer parasitic link and its fuzzy‐based learning controller, which has excellent dynamic and static behavior, for use in a medical X‐ray power generator operating at a wide variety of load settings. The effectiveness of the feasible fuzzy learning technique used for control of the DC–DC power converter is discussed and evaluated based on computer simulations and experimental results in a laboratory setup. It is demonstrated that the feasible fuzzy learning control scheme suitable for this converter is more effective and practical in improving the system output voltage response performance in both transient and steady states for medical‐use X‐ray power generators. The results of simulations and experiments for this converter are presented in order to illustrate the operating performance of the proposed X‐ray power generator operated by the feasible fuzzy‐based learning control implementation. © 2001 Scripta Technica, Electr Eng Jpn, 136(2): 58–71, 2001

Transformer Resonant Phase-Shifted PWM DC-DC Converter for X Ray Power Generator and Its Fuzzy Logic-based Learning Control Scheme

In general, medical-use high-voltage X ray power generator works under a variety of operating conditions of the required output DC voltage and the output current setting values for the X ray tube. A phase-shifted PWM inverter-fed DC-DC power converter with a high-voltage transformer parasitic resonant link which is used for an X ray power generator inherently includes its stiff nonlinear characteristics due to phase-shifted voltage regulation and diode cut off operation in a high-voltage rectifier because of the wide load setting regulation ranges in practical applications. However, superior output voltage response performances of a quick rising time in a transient state and low ripple factor in a steady-state which have to be essentially required for a medical-use X ray power generator could not be sufficiently implemented by various linear modern control approaches because a precise mathematical description with dynamic modeling could not be formulated for wide load variations. For controlling such a nonlinear DC-DC power conversion system, a fuzzy-reasoning-based learning control technique to realize the human capability and much experience to understand the system dynamic and static behavior is more suitable and effective. This paper presents a phase-shifted PWM full bridge inverter type high-voltage DC-DC power converter with a high-voltage transformer parasitic resonant link and its fuzzy-based learning controller, which has excellent dynamic and static behaviors to be utilized in a medical-use X ray power generator operating under conditions of a variety of wide load settings. The effectiveness of feasible fuzzy learning control technique of the DC-DC power converter is discussed and evaluated on the basis of the computer simulation and experimental results in a laboratory set-up. It is proved that the feasible fuzzy-based learning control scheme suitable for this converter is more effective and practical to improve the system output voltage response performances in both the transient and steady states for medical-use X ray power generator. The simulated and experimental results of this converter are actually illustrated in order to substantiate the operating performance validity of the inverter type medical-use X ray power generator operated by the feasible fuzzy-based learning control implementation.

Control Strategies for Unmanned Underwater Vehicles

In recent years, both the offshore industry and the navies of the world have become increasingly interested in the potential operational usage of unmanned underwater vehicles. This paper provides a comprehensive review of a number of modern control approaches and artificial intelligence techniques which have been applied to the autopilot design problem for such craft.

Stabilization of chaotic dynamics: a modern control approach

Modern techniques for dynamic control of chaotic systems are introduced. The problem of controlling chaos is addressed in the same conceptual framework as proposed by Ott, Grebogi and Yorke. However, the novelty here is the introduction of LQ and ℋ∞ techniques to address the problem. These techniques have been tested on representative systems, specifically the Logistic Map.