Control Input Research Articles

Q‐learning‐based H∞ control for LPV systems

AbstractIn this paper, a model‐free H∞ control method is developed for discrete‐time linear parameter‐varying (LPV) systems by leveraging Q‐learning, which employs the data encompassing system states, control inputs, exogenous disturbance, and time‐varying convex hull rather than the dynamical model known a priori. A policy iteration algorithm presented via linear matrix inequality formed by such collected data is developed with convergence guarantee. Our analysis demonstrates that, in the presence of sufficiently rich disturbances, the attenuation level converges to a lower value than the traditional H∞ control solution derived from an exact LPV model. A numerical example is demonstrated to verify the stabilization, disturbance attenuation, adaptivity, and convergence of the H∞ attenuation level. Moreover, a continuous stirred tank reactor (CSTR) approximated by a discrete‐time LPV system is employed to show the practical potential of the developed model‐free approach.

Investigation of metal-insulator-metal waveguides with elliptical-nanodisk resonator for high contrast ratio all-optical logic gates

Abstract This research focuses on the design and analysis of all-optical Exclusive OR(XOR), NOT, and OR logic gates based on metal-insulator-metal waveguides with elliptical-nanodisk resonators. The functionality of the proposed optical logic gates is determined by constructive and deconstructive signals which are applied to the input ports and control ports. To show the logic 0 (low) and logic 1 (high) output states, the limit of threshold transmission is 1.775 × 10−13 ∼0. The transmission (T) and contrast ratio (CR) are obtained to present the performance of the optical logic gates via the method of finite-difference time-domain. The maximum transmission is reached for the OR gate as 1.38 and the highest contrast ratio is 124.75 dB for the XOR and NOT logic gates. The designed logic devices are promising for improving more efficient optical signal information processing devices.

A Method for Evaluating Demand Response Potential of Industrial Loads Based on Fuzzy Control

Demand response (DR) can ensure electricity supply security by shifting or shedding loads, which plays an important role in a power system with a high proportion of renewable energy sources. Industrial loads are vital participants in DR, but it is difficult to assess DR potential because of many complex factors. In this paper, a new method based on fuzzy control is given to assess the DR potential of industrial loads. A complete assessment framework including four steps is presented. Firstly, the industrial load data are preprocessed to mitigate the influence of noisy and transmission losses, and then the K-means algorithm considering the optimal cluster number is used to calculate baseline load of industrial load. Subsequently, an open-loop fuzzy controller is designed to predict the response factor of different industrial loads. Three strongly correlated indicators, namely peak load rate, electricity intensity, and load flexibility, are selected as the input of fuzzy control, which represents response willingness. Finally, the baseline load of diverse clustering scenarios and the response factor are used to calculate the DR potential of different industrial loads. The proposed method takes into account both economic and technical factors comprehensively, and thus, the results better represent the available DR potential in real-world situations. To demonstrate the effectiveness of the proposed method, the case of a medium-sized city in China is studied. The simulation focuses on the top eight industrial types, and the results show they can contribute about 189 MW available DR potential.

Decoupled Model-Free Adaptive Control with Prediction Features Experimentally Applied to a Three-Tank System Following Time-Varying Trajectories

In this paper, the performance of three model-free control approaches on a multi-input, multi-output (MIMO) nonlinear system with constant and time-varying references is compared. The first control algorithm is model-free adaptive control (MFAC). The second is a modified version of MFAC (MMFAC) designed to handle delays in the system by incorporating the output error difference (over two sample time steps) in the control input. The third approach, model-free adaptive predictive control (MFAPC) with a one-step-ahead forecast of the system input, is obtained by using predictions of the outputs based on the data-based linear model. The experimental device used is an MIMO three-tank system (3TS) assumed to be an interconnected system with multiple coupled single-input, single-output (SISO) subsystems with unmeasurable couplings. The novelty of this contribution is that each coupled SISO partition is assumed to be controlled independently using a decoupled control algorithm, leading to fewer control parameters compared to a centralized MIMO controller. Additionally, both parameter tuning for each controller and performance evaluation are conducted using an evaluation criterion considering energy consumption and accumulated tracking error. The results demonstrate that almost all the proposed model-free controllers effectively control an MIMO system by controlling its SISO subsystems individually. Moreover, the predictive features in the decoupled MFAPC contribute to more accurate tracking of time-varying references. The utilization of tracking error differences helps in reducing energy consumption.

A study of multi-model identification and fusion control algorithms for rotary limit devices

In order to improve the control performance of rotating limit device on the motion range of rotating parts of mechanical equipment, the multi model identification and fusion control algorithm of rotating limit device is studied. The angle sensor and speed sensor are used to collect the rotation angle and speed of rotating machinery equipment. Taking the collected data as the input of multiple support vector machines, the D-S evidence theory is selected to fuse the status of rotating machinery equipment identified by multiple models and determine the final status of rotating machinery equipment. Set the deviation between the target angle and the actual angle of the rotating mechanical equipment as the input of the PID controller. The PID controller determines the limit control quantity of the rotating limit device to the rotating machinery equipment, and realizes the rotating limit control of the rotating machinery equipment. The rotary table is selected as the mechanical equipment controlled by the rotary limit device. The experimental results show that the rotary limit device can control the rotation of the rotary table in the ideal angle range, achieve smooth tracking of the rotation angular velocity, and has excellent control performance.

Adaptive hierarchical interval type-2 fuzzy control for trajectory tracking of an underactuated AUV with uncertain dynamics

In this study, an adaptive hierarchical interval type-2 fuzzy control (AHIT2FC) scheme is presented for three-dimensional (3D) trajectory tracking control of an underactuated autonomous underwater vehicle (AUV), which has only three independent control inputs and is subject to partially parametric uncertainty and unknown external disturbances. To decrease reliance on hydrodynamic parameters, an interval type-2 fuzzy logic system (IT2FLS) is utilized, which exhibits superior capabilities in handling high levels of uncertainties prevalent in the underwater environment as compared to a type-1 fuzzy logic system. However, the traditional fuzzy system structure encounters the “curse of dimensionality” issue, which results in high computational complexity and imposes a significant burden on the limited computing resources underwater. The proposed AHIT2FC framework, based on a hierarchical structure, can substantially enhance computational speed while ensuring excellent control performance. Subsequently, Lyapunov’s theory is adopted to guarantee that all the tracking errors in the closed-loop system are semiglobally uniformly bounded (SGUB). Finally, comparative simulation results demonstrate the effectiveness and superiority of the proposed AHIT2FC scheme.

Dynamic Sliding Mode Control of Spherical Bubble for Cavitation Suppression

Cavitation is a disadvantageous phenomenon that occurs when fluid pressure drops below its vapor pressure. Under these conditions, bubbles form in the fluid. When these bubbles flow into a high-pressure area or tube, they erupt, causing harm to mechanical parts such as centrifugal pumps. The difference in pressure in a fluid is the result of varying temperatures. One way to eliminate cavitation is to reduce the radius of the bubbles to zero before they reach high-pressure areas, using a robust approach. In this paper, sliding mode control is used for this purpose due to its invariance property. To force the radius of the bubbles toward zero and prevent chattering, a new dynamic sliding mode control approach is used. In dynamic sliding mode control, chattering is removed by passing the input control through a low-pass filter, such as an integrator. A general model of the spherical bubble is used, transferred to the state space, and then a state proportional-integral feedback is applied to obtain a linear system with a new input control signal. A comparison is also made with traditional sliding mode control using state feedback, providing a trusted comparison.

Adaptive Saturated Obstacle Avoidance Trajectory Tracking Control for Euler–Lagrange Systems With Velocity Constraints

ABSTRACTThis article pays attention to the obstacle avoidance trajectory tracking control problem for uncertain Euler–Lagrange (EL) systems subject to velocity constraints and input saturation. The existing obstacle avoidance results do not consider velocity constraints under input saturation, which means that an EL system may not be able to obtain sufficient control inputs to avoid a collision with an obstacle if it has a high speed when approaching the obstacle. Therefore, the velocity constraints in the obstacle avoidance tracking control are considered in this paper. A novel velocity constraint function that depends on the distance between the system and the obstacle is proposed. Integral‐multiplicative Lyapunov‐barrier functions (LBFs) are constructed and incorporated into the backstepping procedure to design an adaptive fuzzy obstacle avoidance tracking control scheme. Moreover, an auxiliary dynamic system is designed by constructing a bounded nonlinear vector related to an auxiliary variable to compensate for the effects of saturation. Through the Lyapunov method and boundedness analysis for the barrier function, it is shown that the protocol achieves obstacle avoidance for the EL system without violating the velocity constraints inside the obstacle detection region, while also guaranteeing the ultimate uniform boundedness of all the closed‐loop signals. Numerical simulations are presented to demonstrate the efficacy of the proposed control strategy.

Nonideal mixing effect on the input multiplicity and controller performance of CSTR based on Cholette’s model – a simulation study

ABSTRACT The transfer function of the lead-lag process in a CSTR based on Cholette’s model is used to facilitate the input multiplicity analysis. Ideal and nonideal mixing are introduced to investigate the mixing condition effect on the CSTR dynamic behavior. It is verified that the input multiplicity origins include the output multiplicity and the nonideal mixing bypass effect. The former leads to instability in the first-order process, while the latter transforms the first-order process into a lead-lag process and introduces a positive zero transfer function. The start-up diagrams established with both ideal and nonideal mixings are of critical importance to identify the unique and multiple operating regions. We also analyzed the stability conditions based on the pole and the zero of the lead-lag process, which is determined by the nonideal mixing and dominates the behaviors of a real isothermal CSTR with control. The linear and nonlinear integral controller regulatory response simulation results demonstrate that the controller performance could be deteriorated by nonideal mixing.

Integrated Motion Control Strategy Considering Parameter Robustness for Distributed Vehicle by Wire

<div>To address the issues of functional conflicts in execution subsystems and the deterioration of control performance due to model parameter uncertainties in the motion control of distributed vehicle by wire, this article proposes an integrated control strategy considering parameter robustness. This strategy aims to compensate for model mismatch, resolve functional conflicts, and achieve motion coordination. Based on the over-actuation characteristics of distributed vehicle by wire, this article constructs the dynamic model and utilizes the tire cornering properties along with phase portraits to delineate the working regions of the execution subsystems. To deal with model parameter uncertainties and mismatch, tube-based model predictive control (tube-based MPC) is applied to the control strategy design, which compensates for model deviations through state feedback and constructs a robust positively invariant set (RPI) to constrain the system state. Correspondingly, the weights of control inputs are adjusted adaptively, according to the working regions, to optimize the coordination logic of integrated control. In order to verify the effectiveness and feasibility of the strategy, extreme driving condition tests are executed on hardware-in-the-loop (HIL) and real vehicle test platforms. The test results indicate that the strategy proposed in this article is able to reduce the sideslip angle and tracking error of yaw rate, improve driving stability under extreme conditions through integrated control, and especially, it can still maintain precise stability control performance under severe model mismatch, exhibiting strong robustness facing parameter uncertainties.</div>

Research on the potential of integrated vehicle control with closed-loop phase portrait analysis

The phase portrait is an important tool for analyzing vehicle stable region widely utilized in vehicle dynamic control systems. At handling limits, traditional open-loop vehicle stable region constraints will restrict the vehicle control ability, while the closed-loop actuator interventions can help states outside the open-loop stable region converge back to stable origin, which is more suitable for constraining vehicle states under extreme working conditions. This article systematically analyzes the potential of integrated vehicle control with closed-loop phase portrait. Firstly, a vehicle dynamic model considering actuator dynamics and tire transient characteristics is established. Then, a numerical optimal control method for calculating closed-loop controllability region is introduced. The controllability region under different friction coefficients, vehicle speeds, convergence time, vehicle steering response characteristics, actuator time constants, and tire transient characteristics are discussed and analyzed. In terms of different control inputs combinations, this article displays the controllability regions under different front steering angles, rear steering angles, direct yaw moments, and their synergistic performances. Control input laws derived from numerical optimization are summarized in two specific directions. Finally, a comparative analysis of open-loop stable regions and closed-loop controllability regions confirms the superiority of the proposed method. Potential applications of the systematic analysis are also discussed.

Prescribed finite-time safe tracking control based on secure boundary protection method for nonlinear systems with unknown control gains

Aiming to the mutation of the actual output boundary, a prescribed finite-time safe tracking control problem is investigated for a class of nonlinear systems with unknown control gain in this paper. A secure boundary protection method (SBPM) and a new prescribed finite-time performance function (PFTPF) are proposed. The SBPM can construct automatically two adjustable secure boundaries, so that the system meets both the control performance prescribed by the PFTPF and the constraint of the secure boundaries. In order to solve the problem of the excessive jitter of control input caused by the mutation of the output constraint, a bidirectional filtering smoothing mechanism (BFSM) is proposed. The proposed method can effectively deal with the mutation of actual output constraint, and it is not necessary to predict the system output value to adjust the desired output trajectory. Finally, the effectiveness of this proposed method is verified by simulations.

Flatness-based control in successive loops for dual-arm robotic manipulators

Dual-arm robotic manipulators are used in industry and for assisting humans since they enable dexterous handling of objects and more agile and secure execution of pick-and-place, grasping and lifting, or assembling tasks. In this article, a multi-loop flatness-based controller is proposed for the dynamic model of a dual-arm robot. In the considered application, the dual-arm robotic system has to lift and transfer an object under synchronized motion of its two end-effectors while it has also to compensate for the grasping forces between the two end-effectors and the object. The dynamic model of this robotic system is formulated while it is proven that the state-space description of the robot’s dynamics is differentially flat. The control problem for this robotic system is solved with the use of a flatness-based control approach which is implemented in successive loops. To apply the multi-loop flatness-based control method, the state-space model of the dual-arm robotic manipulator is separated into subsystems, which are connected in cascading loops. Each one of these subsystems can be viewed independently as a differentially flat system and control about it can be performed with inversion of its dynamics as in the case of input–output linearized flat systems. The state variables of the preceding i-th subsystem become virtual control inputs for the subsequent ( i + 1)-th subsystem. In turn, real control inputs are applied to the last subsystem. The whole control method is implemented in successive loops and its global stability properties are also proven through Lyapunov stability analysis. The multi-loop flatness-based control approach is an exact nonlinear control scheme which (i) does not use approximate linearization of the dynamic model of the controlled system and (ii) does not need changes of state variables and complicated state-space model transformations.

An intuitive guidewire control mechanism for robotic intervention.

Teleoperated Interventional Robotic systems (TIRs) are developed to reduce radiation exposure and physical stress of the physicians and enhance device manipulation accuracy and stability. Nevertheless, TIRs are not widely adopted, partly due to the lack of intuitive control interfaces. Current TIR interfaces like joysticks, keyboards, and touchscreens differ significantly from traditional manual techniques, resulting in a shallow, longer learning curve. To this end, this research introduces a novel control mechanism for intuitive operation and seamless adoption of TIRs. An off-the-shelf medical torque device augmented with a micro-electromagnetic tracker was proposed as the control interface to preserve the tactile sensation and muscle memory integral to interventionalists' proficiency. The control inputs to drive the TIR were extracted via real-time motion mapping of the interface. To verify the efficacy of the proposed control mechanism to accurately operate the TIR, evaluation experiments using industrial grade encoders were conducted. A mean tracking error of 0.32 ± 0.12mm in linear and 0.54 ± 0.07° in angular direction were achieved. The time lag in tracking was found to be 125ms on average using pade approximation. Ergonomically, the developed control interface is 3.5mm diametrically larger, and 4.5g. heavier compared to traditional torque devices. With uncanny resemblance to traditional torque devices while maintaining results comparable to state-of-the-art commercially available TIRs, this research successfully provides an intuitive control interface for potential wider clinical adoption of robot-assisted interventions.

Incremental robust predictive control for anti-pitching in catamarans with appendage constraints

To solve the problem that high-speed catamarans have excessive amplitude of vertical motion in rough sea conditions, an anti-pitching method based on incremental robust predictive control of catamarans is proposed, which takes into account the model uncertainty and input rate of appendage requirements. Thus, a high-speed catamaran vertical control model is established with T-foils and flaps serving as anti-pitching appendages, and the hydrodynamic coefficient uncertainties is analyzed, which is converted into a state space model with norm-bounded uncertainty to facilitate control system design; moreover, transforming the norm-bounded uncertainty model of a high-speed catamaran into an incremental model, which can increase the integral action to improve the anti-pitching performance. On this basis, the hybrid H2/H∞ robust predictive control method is proposed to achieve wave disturbance resistance capability and robust stability of the catamaran system, taking the rate of input of the anti-pitching appendages as the input constraints, and the linear matrix inequality (LMI) receding-horizon optimization is used to solve the incremental control input of appendages. Ultimately, the effectiveness of the proposed algorithm is verified by digital simulation.

H ∞ bumpless transfer control for switched affine systems with its application to turbofan engine model

Switched affine systems (SASs) are a special class of switched systems. The existing works about SASs predominantly focuses on steady-state performance. There exist limited attention given to transient performance, particularly the transient performance induced by switchings. The inappropriate switchings can induce severe signal jumps, degrade the steady-state performance of the system, and even lead to instability. The bumpless transfer control (BTC) represents an effective strategy for mitigating signal jumps. However, the existing BTC methods are primarily designed for general switched systems, and these approaches are often not applicable to SASs. This article is focussed on the issue of H ∞ BTC for SASs under unmodeled disturbances. Firstly, an affine term (AT) related to H ∞ bumpless transfer (BT) performance definition is introduced for the SAS to characterise the alleviation level of the bumps in the control input signal at switching points. Secondly, a criterion is established to enable the solvability of the H ∞ BTC problem for the SAS. Thirdly, an H ∞ BT controller and a switching signal are co-designed to drive the SAS to satisfy the H ∞ BT performance which may not be shared by the subsystems. Finally, a turbofan engine model example is implemented to illustrate the availability and rationality of the suggested H ∞ BTC scheme.

Aging-aware co-optimization of topology, parameter and control for multi-mode input- and output-split hybrid electric powertrains

Existing research has focused on battery intrinsic optimization, Hybrid Energy Storage System (HESS), and powertrain control perspectives to enhance battery life. However, the impact of powertrain physical architecture -control multi-layer co-optimization on battery life has been neglected. Therefore, this study innovatively proposes a multi-mode dedicated hybrid transmission (DHT)—from the perspective of powertrain architecture—to reduce battery life degradation by switching between input split (IS) and output split (OS) modes. In order to fully optimize the battery degradation potential, a topology-parameter-control multi-layer co-optimization (TPCMC) method is proposed in this paper. In the topology layer, graph theory method is used for automatic generation, screening and modeling. In the parameter and control layer, a novel near-optimal energy management strategy, Rapid Dynamic Programming+ (Rapid-DP+), is proposed by introducing Pareto optimization, slope filtering, and Battery Life Aging Optimization (BLAO) methods, which improves the computational efficiency by 3500 times with 9.09–21.1 % battery life optimization. The results show that, relative to the Toyota Prius, the optimized powertrain improves the acceleration by 41.3 %, fuel economy by 6.08 %–8.1 %, and battery life degradation by 9.9 %–22.5 % under different driving cycles. This paper contributes to battery life degradation in the electrified transportation through an advanced TPCMC approach.

Co-application of fly ash and zeolite increases N uptake but decreases P uptake and biomass of rice fertilized with fermented liquid manure

ABSTRACT Fermented liquid pig manure (LPM) can be used as a nutrient source to replace synthetic fertilizers (SF). However, concerns remain regarding nitrogen (N) and phosphorus (P) losses from rice (Oryza sativa L.) paddies fertilized with LPM. Fly ash (FA) has a high calcium content (Ca) and zeolite (Z) has a high negative-charge; thus, they can immobilize P and N through the fixation of P with Ca and NH4 + onto negatively charged sites, respectively. This study investigated the effects of the co-application of FA and Z (FAZ) on the nutrient availability and growth of rice fertilized with LPM. Four treatments were evaluated: no input (control), synthetic fertilizer (SF), and LPM at two levels, with or without FAZ application, for 104 days. The pH (pHwater), electrical conductivity (ECwater), N (Nwater), and P (Pwater) concentrations in the ponding water of rice fields were analyzed 18 times during rice growth. The rice biomass and uptake of N and P were measured, and the concentrations of mineral N and available P in soil were determined after harvest. LPM application increased (p < 0.001) N and P availability in the absence of FAZ, leading to rice biomass comparable to that of SF. However, FAZ diminished the fertilization effects of LPM on rice growth. The Nwater decreased by 50% and the rice uptake of N increased by 6% after FAZ application, probably because of the retention of N by Z and its subsequent release. By contrast, FAZ increased (p < 0.001) soluble Pwater (85% for LPMS) and decreased (p = 0.004) P uptake (8%–40%), reducing the rice biomass by 20%–25%. The decreased P uptake is probably due to the strong immobilization of P by FA. Therefore, it is cautioned that P-limitation through immobilization of P by FA under alkaline conditions may hinder rice growth in FAZ-amended paddy fertilized with LPM. An appropriate application rate of FA for improved P nutrition needs to be explored.

A Memristor-Based Circuit with the Loser-Take-All Mechanism for Classification

Traditional multi-class classification circuits mostly use the mechanism of winner-take-all. In this paper, a memristor-based classification circuit with the loser-take-all mechanism is designed. The winner-take-all mechanism selects the most active neuron or signal while suppressing others, whereas the loser-take-all mechanism suppresses the most active and amplifies weaker signals. The goal of the loser-take-all mechanism is to determine which class an item does not belong to, rather than to determine which class the item belongs to. The loser-take-all mechanism can use relatively undemanding criteria to correctly classify the majority of categories that are misclassified by the winner-take-all mechanism. The designed circuit includes input modules, control modules and suppression modules which realize the multi-classification function based on the loser-take-all mechanism. The simulation results in Cadence show that the circuit can be used to realize complicated classification applications. The memristor-based classification circuit with the loser-take-all mechanism can capture the subtle nuances of various categories and provide a flexible approach to classification tasks.

Closed-loop workload input–output control of production systems: A hybrid simulation study

Workload Control (WLC) is a method of adjusting the overall workload in the production system by controlling the input of production orders and the output of produced items. It contributes to the predictability of lead times and more accurate delivery date commitments in make-to-order manufacturing. Input control relates to order release and output control to capacity adjustment. In a recent previous work, a novel approach to integrated input–output control has been proposed: a dynamic closed-loop model where automatic feedback control is added and where order release and capacity decisions are based on the observed shop floor state. In this paper, this approach is further investigated in a more realistic hybrid simulation setting, combining discrete-time controllers and a discrete-event model of a manufacturing shop. The hybrid model was applied to two different systems: an elementary 4-machine shop floor (as a proof of concept) and a more complex real system, a manufacturing cell of cylinder liners. The results show that simultaneous input–output control is effective and enables the systems to maintain WIP balance, absorb demand fluctuations, and effectively reject disturbances. The simulations of the complex system showed that it might be advantageous to provide more local or more global information to the controllers, depending on the variability of the processing times and on the managerial focus. Closed-loop discrete-event models for WLC production control are unprecedented. Also, a simultaneous input and output control setting is much less reported in WLC literature than settings with input control only (i.e., order release only). This paper contributes in both ways.