Desired Control Research Articles

Semi-Active Vibration Control of Seat Suspension Equipped with a Variable Equivalent Inertance-Variable Damping Device

The seat suspension has a significant influence on riding comfort in many practical applications, such as heavy duty vehicles, military vehicles, and high-speed crafts. This paper proposes a seat suspension equipped with a variable equivalent inertance-variable damping (VEI–VD) device and a novel semi-active vibration control strategy. The VEI–VD device can control its equivalent inertance and damping by controlling two external resistors in its electric circuit. Especially, the VEI part of the device can store and release vibration energy via the inside flywheel, which enables the seat suspension to have a four-quadrant controllable capability in the available force–velocity diagram, similar to an active system. First, the dynamic model of the VEI–VD device is built, and a prototype is developed and tested to identify the model parameters and verify its characteristics. Then, a semi-active vibration control method is proposed for the VEI–VD seat suspension. The control method uses a sliding mode controller to acquire the desired control force for reducing vibration; then, according to the desired force and system states, the VEI–VD device is tuned by a force-tracking scheme to generate a real force. In the numerical validation, the vibration transmissibility of VEI–VD seat suspension around its natural frequency is tested with different states. The effectiveness of force-tracking control strategies for different types of suspensions is verified. In the random excitation test, the root means square acceleration of the VEI–VD seat is reduced by 30.72% compared with a passive seat. The VEI–VD seat suspension shows great potential in applications.

Using synthesis to steer excited states and their properties and functions

The nature, properties and reactivities of ground-state molecules have been studied widely. By contrast, the parallel manipulation and knowledge of molecules in their excited states are not well controlled or understood. Here we have investigated the manipulation and control of excited-state molecules, with the generation of libraries of molecules. The power and ability of light to drive chemical reactions, conformational changes, motion, luminescence and energy conversions in nature have inspired researchers to harness excited states to achieve the desired control of manipulation of molecules in their excited state to tackle challenges in materials and energy research and sustainability. To this end, synthesis can be used to harness excited states and molecular functional materials. Furthermore, supramolecular chemistry can provide an additional dimension of control to the excited states and expand the library of excited-state functional materials. By mastering the design of excited states, an in-depth understanding and discovery of excited states with desirable properties and controllable transformation by design may open up a new area of research, resulting in libraries of excited-state molecules and chemistry that parallel ground-state chemistry and, in doing so, offer unlimited opportunities.

Distributed dynamic event-based finite-time dissipative synchronization control for semi-Markov switched fuzzy cyber-physical systems against random packet losses

This paper is concerned with the finite-time dissipative synchronization control problem of semi-Markov switched cyber-physical systems in the presence of packet losses, which is constructed by the Takagi–Sugeno fuzzy model. To save the network communication burden, a distributed dynamic event-triggered mechanism is developed to restrain the information update. Besides, random packet dropouts following the Bernoulli distribution are assumed to occur in sensor to controller channels, where the triggered control input is analyzed via an equivalent method containing a new stochastic variable. By establishing the mode-dependent Lyapunov–Krasovskii functional with augmented terms, the finite-time boundness of the error system limited to strict dissipativity is studied. As a result of the help of an extended reciprocally convex matrix inequality technique, less conservative criteria in terms of linear matrix inequalities are deduced to calculate the desired control gains. Finally, two examples in regard to practical systems are provided to display the effectiveness of the proposed theory.

Research on Control Strategy of Electro-Hydraulic Lifting System Based on AMESim and MATLAB

Given the influence of flow instability, parameter uncertainty, and unpredictable disturbances in electro-hydraulic lifting systems, high-precision position control for electro-hydraulic lifting systems is challenging to achieve. This study proposes an observer–sliding mode control strategy to improve the control accuracy of the tractor electro-hydraulic lifting system. Firstly, the principle of the electro-hydraulic hoisting system is analyzed. Secondly, a mathematical model of the electro-hydraulic hoisting system is established, and the electro-hydraulic hoisting system is reduced to design an observer to achieve a real-time evaluation of the unknown system state and disturbance. The observer and the sliding mode control are then integrated into a controller to improve system response. Theoretical analysis demonstrates that the controller ensures that the actuator can achieve the desired control effect even under disturbing effects. Finally, a joint AMESim–MATLAB simulation and conducting pilot studies are carried out to compare the observer–sliding mode control with PID (Proportion–Integral–Derivative) control and sliding mode control. At the same time, in the process of the simulation and test, the symmetric structure as the electro-hydraulic lifting system was used to build a ploughing depth simulation system (changes in the hydraulic cylinder thrust simulate changes in ploughing depth values). The results show that the proposed observer–sliding mode control strategy can achieve a better position and pressure tracking and parameter change robustness than PID control and sliding mode control.

Generalized Variable Gain ADRC for Nonlinear Systems and Its Application to Delta Parallel Manipulators

In this paper, a novel generalized variable gain active disturbance rejection control (VGADRC) method is proposed for the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> -th order nonlinear system. The generalized VGADRC, including generalized variable gain tracking differentiator (VGTD), generalized variable gain extended state observer (VGESO), and generalized variable gain controller (VGC), incorporates error-based variable gains to achieve desired control performance. Moreover, the stability analysis of VGADRC is performed, and the existence of feasible solutions are discussed and expressed explicitly. Finally, the generalized VGADRC method is applied to delta parallel manipulators, and the numerical simulation results and experiment results are presented to illustrate the effectiveness of the proposed method.

Adaptive Model Predictive Control of an Interleaved Boost Converter Using Real-Time Updated Model

To optimize the voltage regulation performance and enhance the robustness, an adaptive model predictive controller is proposed in this article for an interleaved dc–dc boost converter. The predictive model is constructed by linearizing the nonlinear equations of the converter at the current operating point. A novel parameter update mechanism is developed based on the static model, which enables fast and accurate identification of the model parameters, thus the control law can guarantee the desired control performance in the wide operating range. Based on the adaptive model, a disturbance observer is constructed to correct the model predictions and mitigate parameter uncertainties. Then an explicit control law is derived by solving the optimization problem offline, and the stability analysis is carried out using the linear control theory. Finally, the effectiveness of the proposed method is verified by both simulation and experimental results.

Explaining the “Mystery” of Periodicity in Inter-Transmission Times in Two-Dimensional Event-Triggered Controlled Systems

Motivated by scenarioswhere the communication or the computation resources are limited, event-triggered control consists of transmitting data between the plant and the controller according to the actual system needs and not the elapsed time since the last transmission instant as in traditional sampled-data control, so that the desired control objective is achieved. A range of techniques are nowadays available to design event-triggered controllers. However, we generally have only very little information about the actual behavior of the transmission instants and thus about the amount of transmissions being actually generated, though this is a key feature of the design. In this article, we analyze the inter-event times, i.e., the times between two successive transmission instants, when the plant is modeled as a two-dimensional linear time-invariant system. The controller is a state-feedback law and the triggering rule is the relative threshold policy, which is allowed to be time-regularized. One of the main results in this article is the explanation of the oscillatory behavior of the inter-event times when the constant used to define the threshold is small relative to 1, a phenomenon commonly observed in simulations but never explained so far. More generally, the presented results help to understand the behavior of the inter-event times, instead of solely relying on numerical simulations, and thereby can be exploited to rigorously evaluate the performance of the considered triggering condition in terms of (average) inter-transmission times.

Inverse Application of Artificial Intelligence for the Control of Power Converters

This article proposes a novel application method, inverse application of artificial intelligence (IAAI) for the control of power electronic converter systems. The proposed method can give the desired control coefficients/references in a simple way because, compared to conventional methods, IAAI only relies on a data-driven process with no need for an optimization process or substantial derivations. Noting that the IAAI approach uses artificial intelligence to provide feasible coefficients/references for the power converter control, rather than building a new controller. After illustrating the IAAI concept, a conventional application method of artificial neural network is discussed, an optimization-based design. Then, a two-source-converter microgrid case is studied to choose the best droop coefficients via the optimization-based approach. After that, the proposed IAAI method is employed for the same microgrid case to quickly find good droop coefficients. Furthermore, the IAAI method is applied to a modular multilevel converter (MMC) case, extending the MMC operation region under unbalanced grid faults. In the MMC case, both simulation and experimental online tests validate the operation, feasibility, and practicality of IAAI.

A Novel State-of-Charge-Based Droop Control for Battery Energy Storage Systems to Support Coordinated Operation of DC Microgrids

A modern dc microgrid often comprises renewable energy sources (RESs), such as photovoltaic (PV) generation units, battery energy storage systems (BESSs), and local load, and it is also connected to the utility grid through a point of common coupling (PCC). While most existing approaches have to rely on communication links to achieve the desired control performance, this article proposes a novel control strategy without resorting to the communication links. This is achieved by assigning BESSs as master units and regulating the dc bus voltage with a novel state-of-charge (SoC)-based droop control, where the BESSs coordinate the slave units (e.g., RES and utility grid) with the aid of the dc bus signaling (DBS) technique to avoid overcharging and overdischarging of these BESSs. In the proposed droop control, the reference voltage for these BESSs is designed for coordinated operation between BESSs and utility grid, and it is maintained constant in the normal SoC range, which can reduce dc voltage variation. Droop coefficients designed for SoC balance of BESSs are dynamically adjusted based on their own SoC values. Furthermore, the preset maximum deviation between the reference voltage and the dc bus voltage ensures the reliable coordinated operation. Real-time hardware-in-loop (HIL) tests considering three different scenarios are conducted to validate the effectiveness of the proposed method.

Stable Inverse Dynamics for Feedforward Control of Nonminimum-Phase Underactuated Systems

Abstract An enhanced inverse dynamics approach is here presented for feedforward control of underactuated multibody systems, such as mechanisms or robots where the number of independent actuators is smaller than the number of degrees of freedom. The method exploits the concept of partitioning the independent coordinates into actuated and unactuated ones (through a QR-decomposition) and of linearly combined output, to obtain the internal dynamics of the nonminimum-phase system and then to stabilize it through proper output redefinition. Then, the exact algebraic model of the actuated sub-system is inverted, leading to the desired control forces with just minor approximations and no need for pre-actuation. The effectiveness of the proposed approach is assessed by three numerical test cases, by comparing it with some meaningful benchmarks taken from the literature. Finally, experimental verification through an underactuated robotic arm with two degrees of freedom is performed.

Distributed cooperative control with collision avoidance for spacecraft swarm reconfiguration via reinforcement learning

This article investigates an adaptive, distributed, and cooperative control strategy for the problem of spacecraft swarm reconfiguration, which involves assembling the spacecraft at a close distance to one another while avoiding collisions and keeping spacecraft far from an obstacle. The key idea is to transform their opposite indices into equivalent ones by using soft and hard constraints. The proposed control strategy is inspired by the actor–critic framework of reinforcement learning (RL) algorithms: The soft constraint is designed by using a critic neural network (NN) for assembling and avoiding obstacles, while collisions among the spacecraft are prevented based on the hard constraint established in an artificial potential field (APF). By drawing support from this idea of equivalent transformation, the adaptive, distributed, and cooperative controller is devised by using an actor NN of the RL algorithm, an APF, and Backstepping control technology. The action NNs are used to estimate the input signals of the desired control and the undesired effects due to disturbance from the APF, and the expected control performance is then obtained by minimizing the output of the critic NN. The computational burden incurred by the NNs is significantly reduced by reducing the number of parameters that need to be learned by NNs. Lyapunov stability theory is used to guarantee that all signals in this closed-loop system are ultimately uniformly bounded to ensure its stability. The results of simulations of a swarm of spacecraft demonstrated the effectiveness of the proposed control strategy.

MODI: A Structured Development Process of Mode-Based Control Algorithms in the Early Design Stage of Building Energy Systems

The growing share of renewable energy sources in building energy systems leads to more complex energy conversion and distribution systems. The current process of developing appropriate control functions for energy systems is insufficient and consequently error-prone. Regarding this problem, a new method is expected to systematically develop appropriate control functions for buildings and reduce design errors in this process. This paper introduces the MODI method, aiming at a structured development process of mode-based control algorithms to reduce errors in the early design stages of buildings. A complete framework and a standardized application process of the MODI method will be established to systematically design mode-based control algorithms described through signal-interpreted Petri nets. Furthermore, we performed a simulation-assisted evaluation approach to test and improve the performance of the control algorithms generated by MODI. In a case study, we applied MODI to develop a mode-based control strategy for an energy system containing heating and cooling supply networks. The desired control strategy was tested and tuned in a simulation phase. Compared to a reference control, the mode-based control algorithm shows an improvement in system efficiency by 4% in winter and 8% during the transitional season phase.

Consensus control for multi-rate multi-agent systems with fading measurements: the dynamic event-triggered case

This paper studies the distributed -consensus control problem for a class of multi-rate multi-agent systems with fading measurements. A multi-rate sampling strategy is adopted to be more in line with actual need and the channels between each agent and its sensor always fade non-identically. The multi-rate system is transformed into a single-rate system via the lifting technique. For the purpose of reducing the transmission burden, a dynamic event-triggered mechanism is utilized to determine whether the agent's information is allowed to transmit to its neighbours. This paper aims to design an observer-based event-triggered controller for each agent to achieve the -consensus control performance constraint. With the help of the Lyapuonv stability theory, sufficient conditions are obtained that can ensure the desired control performance for the resulting closed-loop systems, and then the desired gain matrices are calculated by solving the linear matrix inequality. Finally, a numerical simulation example is given to demonstrate the effectiveness of the distributed event-triggered consensus control scheme.

INSULIN THERAPY IN T2DM PATIENTS IN DIABETES OUTPATIENT CLINIC, DR. SOETOMO GENERAL ACADEMIC HOSPITAL, SURABAYA, INDONESIA

Highlights1. The occurrence of macrovascular and microvascular problems is strongly associated with high mortality in type 2 diabetes mellitus (T2DM).2. Combinations of rapid-acting and long-acting insulin were the most frequent kind of insulin. AbstractBackground: High mortality in type 2 diabetes mellitus (T2DM) has a strong correlation with the presence of macrovascular and microvascular complications. The risk of these complications can be reduced through good glycemic control. As the disease progresses, patients may need to add or switch to insulin therapy rather than oral antihyperglycemic drugs to achieve desirable glycemic control. Objective: To determine the pattern of insulin therapy and glycemic control in T2DM patients. Material and Method: Data for this study were obtained from the medical records of the Diabetes Outpatient Clinic at the Dr. Soetomo General Academic Hospital, Surabaya, Indonesia. This study was an observational descriptive. In June-July 2016, total samples were collected from 124 patients who received insulin therapy between February 2015 and March 2015. Result: According to the data obtained, the most commonly used insulin was a combination of rapid-acting and long-acting insulin (75.8%). While basal bolus insulin (75.8%) accounts for the most common regimen used to administer insulin, only 27.4% and 45% of total patients achieved good glycemic control based on FPG and PPG testing, respectively. HbA1c testing was done on 44 out of 124 people, with 9 people (20.5%) met the target of HbA1c &lt;7%. Conclusion: Glycemic control in T2DM patients who received insulin therapy was relatively low.

Event-triggered sliding mode control for networked linear systems

This paper investigates the control-based event-triggered sliding mode control for a networked linear system whose feedback information is transmitted over a digital communication network. In this paper, a novel event-triggered mechanism based on control value is proposed. Different from traditional event-triggered mechanisms that are normally based on states, our mechanism pays more attention to the desired control input value of the system. When the deviation between the current control input and the control input being calculated on the basis of the previous system state exceeds a given threshold, an event is triggered. For the sake of reducing the information to be transmitted, a quantization policy is executed and only a few bits are needed to transmit the feedback symbol of each sample. The combination of the control-based event-triggered mechanism and the quantization policy can significantly reduce both the transmission frequency and the number of bits of each feedback packet. For the concerned system, sliding mode control is implemented. The reachability of the sliding mode surface and the robust stability of the system are analyzed by fully taking quantization effects into account. Moreover, the effects of transmission delay of feedback packets on the event-triggering mechanism are considered. Under the proposed mechanism, the lower bound of event intervals is proven to be non-zero, i.e., the Zeno behavior is excluded. Simulations of a mechanical system are done to further verify the superiority of the proposed mechanism.

A Novel Exploration-Exploitation-Based Adaptive Law for Intelligent Model-Free Control Approaches.

Model-free control approaches require advanced exploration-exploitation policies to achieve practical tasks such as learning to bipedal robot walk in unstructured environments. In this article, we first construct a comprehensive exploration-exploitation policy that carries quality knowledge about the long-term predictor and the control policy, and the control signal of the model-free algorithms. Therefore, the developed model-free algorithm continues exploration by adjusting its unknown parameters until the desired learning and control are accomplished. Second, we provide an utterly model-free adaptive law enriched with the exploration-exploitation policy and derived step-by-step using the exact analogy of the model-based solution. The obtained adaptive control law considers the control signal saturation and the control signal (input) delay. Performed Lyapunov stability analysis ensures the convergence of the adaptive law that can also be used for intelligent control approaches. Third, we implement the adaptive algorithm in real time on a challenging benchmark system: a fourth-order, coupled dynamics, input saturated, and time-delayed underactuated manipulator. The results show that the proposed adaptive algorithm explores larger state-action spaces and treats the vanishing gradient problem in both learning and control. Also, we notice from the results that the learning and control properties of the adaptive algorithm are optimized as required.

Nonvolatile electro-mechanical coupling in two-dimensional lattices.

Electro-mechanical coupling is of great interest for applications in sensors, actuators and energy harvesters. While the control of electrical charge by mechanical force has been studied extensively, reverse coupling is rarely explored, especially in two-dimensional (2D) lattices. Herein, we propose a novel mechanism for electro-mechanical coupling that realizes the electric field switching of the dimensions of a 2D lattice in a reversible and nonvolatile fashion, through the mediated strength of interlayer interactions in ferroelectric bilayer systems. Based on first-principles calculations, the validity of this mechanism is demonstrated in a series of real bilayer materials, i.e., MoS2/ReIrGe2S6, Sb/In2Se3 and bilayer In2Se3. The interface differences due to polarization play a crucial role in realizing such nonvolatile electro-mechanical coupling, and the underlying physical origin is discussed. These explored phenomena and insights offer a novel avenue for the highly desired nonvolatile electric field control of mechanical strain.

A Hierarchical MPC Approach to Car-Following via Linearly Constrained Quadratic Programming

Single-lane car-following is a fundamental task in autonomous driving. A desirable car-following controller should keep a reasonable range of distances to the preceding vehicle and do so as smoothly as possible. To achieve this, numerous control methods have been proposed: some only rely on local sensing; others also make use of non-local downstream observations. While local methods are capable of attenuating high-frequency velocity oscillation and are economical to compute, non-local methods can dampen a wider spectrum of oscillatory traffic but incur a larger cost in computing. In this letter, we design a novel non-local tri-layer MPC controller that is capable of smoothing a wide range of oscillatory traffic and is amenable to real-time applications. At the core of the controller design are 1) an accessible prediction method based on ETA estimation and 2) a robust, light-weight optimization procedure, designed specifically for handling various headway constraints. Numerical simulations suggest that the proposed controller can simultaneously maintain a variable headway while driving with modest acceleration and is robust to imperfect traffic predictions.

Formation Control for Leader–Follower Wheeled Mobile Robots Based on Embedded Control Technique

The formation control problem for leader–follower wheeled mobile robots (WMRs) is investigated in this article. A formation control strategy is proposed based on the embedded control technique. Different from the conventional design philosophy of designing the formation controller based on the formation tracking errors directly, the proposed strategy decomposes the formation control task into two subtasks. One is the virtual signal generator (i.e., virtual follower) design, and the other is the trajectory tracking controller design. The virtual signal generator is devised to act as a virtual follower such that it “achieves” the desired formation control goal, whose output is taken as the reference trajectory for the follower. To solve the subtask of trajectory tracking controller design, an unconstrained controller and a constrained controller with saturated velocities are designed, respectively. A rigorous stability analysis of the closed-loop system is given under these two kinds of controllers. Comparative simulations and experiments among the unconstrained controller with higher gains/lower gains and the constrained controller are given to illustrate the feasibility and effectiveness of the proposed formation control strategy.

Relative controllability of conformable delay differential systems with linear parts defined by permutable matrices

We study relative controllability of linear and nonlinear conformable delay differential systems with linear parts defined by permutable matrices. By using a notion of delay Grammian matrix, we give a sufficient and necessary condition to examine that a linear delay controlled systems is relatively controllable. Thereafter, we construct a suitable control function for nonlinear delay controlled system, which admits us to adopt the framework of fixed point methods to investigate the same issue. More precisely, we apply Krassnoselskii?s fixed point theorem to derive a relative controllability result. Finally, two examples are presented to illustrate our theoretical results with the help of computing the desired control functions and inverse of delay Grammian matrix as well.