Application of Linear Model Predictive Control and Input-Output Linearization to Constrained Control of 3D Cable Robots

Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging compared to parallel robots. This paper introduces a controller for cable robots under force constraint. The controller is based on input-output linearization and linear model predictive control. Performance of input-output linearizing (IOL) controllers suffers due to constraints on input and output variables. This problem is successfully tackled by augmenting IOL controllers with linear model predictive controller (LMPC). The effecttiveness of the proposed method is illustrated by numerical simulation.

Nonlinear Control of Induction Motor： A Combination of Nonlinear Observer Design and Input-Output Linearization Technique

This paper deals with a nonlinear control strategy of induction motor that combines an input-output linearization control technique and a nonlinear observer design. It is well known that induction motors are the most widely used motors in electrical appliances, industrial control and automation. However, it is also known that induction motor control is a complex task that is due to its nonlinear characteristics. Two main features of the proposed approach are worth to be mentioned. Firstly, a nonlinear control is carried out using a nonlinear feedback linearization technique involving non available state variable measurements of the induction motor system. Secondly, a nonlinear observer is designed to estimate these pertinent but unmeasurable state variables of the machine. The circle-criterion approach is performed to compute the observer gain matrices as a solution of LMI （linear matrix inequalities） that ensure the stability conditions, in the sense of Lyapunov, of the estimated state error dynamics of the designed observer. Simulation results are presented to validate the effectiveness of the proposed approach.

Input-output approach to robust stability and stabilization for uncertain singular systems with time-varying discrete and distributed delays

Based on input-output approach, the robust stability and stabilization problems for uncertain singular systems with time-varying delays are investigated. The parameter uncertainties are assumed to be norm-bounded and the time-varying delays include both discrete delay and distributed delay. By introducing a new input-output model, the time-delay system is embedded in a family of systems with a forward system without time delay and a dynamical feedback uncertainty. A sufficient and necessary condition, which guarantees the system regular, impulse-free and stable for all admissible uncertainties, is obtained. Based on the strict linear matrix inequality, the desired robust state feedback controller is also obtained. Finally, a numerical example is provided to demonstrate the application of the proposed method.

Least Squares Solution for Discrete Time Nonlinear Stochastic Optimal Control Problem with Model-Reality Differences

In this paper, an efficient computational approach is proposed to solve the discrete time nonlinear stochastic optimal control problem. For this purpose, a linear quadratic regulator model, which is a linear dynamical system with the quadratic criterion cost function, is employed. In our approach, the model-based optimal control problem is reformulated into the input-output equations. In this way, the Hankel matrix and the observability matrix are constructed. Further, the sum squares of output error is defined. In these point of views, the least squares optimization problem is introduced, so as the differences between the real output and the model output could be calculated. Applying the first-order derivative to the sum squares of output error, the necessary condition is then derived. After some algebraic manipulations, the optimal control law is produced. By substituting this control policy into the input-output equations, the model output is updated iteratively. For illustration, an example of the direct current and alternating current converter problem is studied. As a result, the model output trajectory of the least squares solution is close to the real output with the smallest sum squares of output error. In conclusion, the efficiency and the accuracy of the approach proposed are highly presented.

Observer-Based Nonlinear Feedback Controls for Heartbeat ECG Tracking Systems

The analysis and design of observed-based nonlinear control of a heartbeat tracking system is investigated in this paper. Two of Zeeman’s heartbeat models are investigated and modified by adding the control input as a pacemaker, thereby creating the control-affine nonlinear system models that capture the general heartbeat behavior of the human heart. The control objective is to force the output of the heartbeat models to track and generate a synthetic electrocardiogram (ECG) signal based on the actual patient reference data, obtained from the William Beaumont Hospitals, Michigan, and the PhysioNet database. The formulations of the proposed heartbeat tracking control systems consist of two phases: analysis and synthesis. In the analysis phase, nonlinear controls based on input-output feedback linearization are considered. This approach simplifies the difficult task of developing nonlinear controls. In the synthesis phase, observer-based controls are employed, where the unmeasured state variables are estimated for practical implementations. These observer-based nonlinear feedback control schemes may be used as a control strategy in electronic pacemakers. In addition, they could be used in a software-based approach to generate a synthetic ECG signal to assess the effectiveness of diagnostic ECG signal processing devices.

Robust Input-Output Energy Decoupling for Uncertain Singular Systems

This paper addresses the robust input-output energy decoupling problem for uncertain singular systems in which all parameter matrices except E exist as time-varying uncertainties. By means of linear matrix inequalities (LMIs), sufficient conditions are derived for the existence of linear state feedback and input transformation control laws, such that the resulting closed-loop uncertain singular system is generalized quadratically stable and the energy of every input controls mainly the energy of a corresponding output, and influences the energy of other outputs as weakly as possible. Keywords Uncertain singular systems - generalized quadratical stability - input-output energy decoupling - linear matrix inequality (LMI) Xin-Zhuang Dong graduated from the Institute of Information Engineering of People’s Liberation Army, China, in 1994. She received the M. S. degree from the Institute of Electronic Technology of People’s Liberation Army, in 1998 and the Ph.D. degree from Northeastern University, China, in 2004. She is currently a post-doctoral fellow at the Key Laboratory of Systems and Control, CAS.Her research interests include singular and nonlinear systems, especially the control of singular systems such as H ∞ control, passive control and dissipative control. Qing-Ling Zhang received the Ph.D. degree from Northeastern University, China, in 1995. He is currently a professor with the Institute of Systems Science, Northeastern University. His research interests include singular systems, fuzzy systems, decentralized control, and H 2/H ∞ control.

Decoupling Zeros of Positive Discrete-Time Linear Sys-tems

The notions of decoupling zeros of positive discrete-time linear systems are introduced. The relationships between the decoupling zeros of standard and positive discrete-time linear systems are analyzed. It is shown that: 1) if the positive system has decoupling zeros then the corresponding standard system has also decoupling zeros, 2) the positive system may not have decoupling zeros when the corresponding standard system has decoupling zeros, 3) the positive and standard systems have the same decoupling zeros if the rank of reachability (observability) matrix is equal to the number of linearly independent monomial columns (rows) and some additional assumptions are satisfied.

A Stable Analytical Solution Method for Car-Like Robot Trajectory Tracking and Optimization

In this paper, the car-like robot kinematic model trajectory tracking and control problem is revisited by exploring an optimal analytical solution which guarantees the global exponential stability of the tracking error. The problem is formulated in the form of tracking error optimization in which the quadratic errors of the position, velocity, and acceleration are minimized subject to the rear-wheel car-like robot kinematic model. The input-output linearization technique is employed to transform the nonlinear problem into a linear formulation. By using the variational approach, the analytical solution is obtained, which is guaranteed to be globally exponentially stable and is also appropriate for real-time applications. The simulation results demonstrate the validity of the proposed mechanism in generating an optimal trajectory and control inputs by evaluating the proposed method in an eight-shape tracking scenario.

Following Control for a UUV using Temporary Path Generation Guidance

A path following control algorithm for an unmanned underwater vehicle（UUV） using temporary path generation guidance was proposed in this paper.Owing to different initial states of the vehicle,such as position and orientation,the path following control in the horizontal plane may yield a poor performance.To deal with the negative effect induced by initial states,a temporary path generation was presented based on the relationship between the original reference path and the vehicle’s initial states.With different relative positions between the vehicle and reference path,including out of straight lines,as well as inside and outside a circle,the related temporary paths guiding the vehicle to the reference path were able to be generated in real time.The vehicle was guided to steer along the temporary path until it reached the tangent point at the reference path,where the controller was designed using the input-output feedback linearization method.Simulation results demonstrated that the proposed algorithm is effective under the three different situations mentioned above.

Electronic Throttle Control System: Modeling, Identification and Model-Based Control Designs

Electronic throttle control (ETC) system has worked its way to becoming a standard subsystem in most of the current automobiles as it has contributed much to the improvement of fuel economy, emissions, drivability and safety. Precision control of the subsystem, which consists of a dc motor driving a throttle plate, a pre-loaded return spring and a set of gear train to regulate airflow into the engine, seems rather straightforward and yet complex. The difficulties lie in the unknown system parameters, hard nonlinearity of the pre-loaded spring that pulls the throttle plate to its default position, and friction, among others. In this paper, we extend our previous results obtained for the modeling, unknown system parameters identification and control of a commercially available Bosch’s DV-E5 ETC system. Details of modeling and parameters identification based on laboratory experiments, data analysis, and knowledge of the system are provided. The parameters identification results were verified and validated by a real-time PID control implemented with an xPC Target. A nonlinear control design was then proposed utilizing the input-output feedback linearization approach and technique. In view of a recent massive auto recalls due to the controversial uncontrollable engine accelerations, the results of this paper may inspire further research interest on the drive-by-wire technology.

Input-output finite-time stability of time-varying linear singular systems

This paper studies the input-output finite-time stabilization problem for time-varying linear singular sys- tems. The output and the input refer to the controlled output and the disturbance input, respectively. Two classes of dis- turbance inputs are considered, which belong to L-two and L-infinity. Sufficient conditions are firstly provided which guarantee the input-output finite-time stability. Based on this, state feedback controllers are designed such that the resultant closed-loop systems are input-output finite-time stable. The conditions are presented in terms of differential linear matrix inequalities. Finally, an example is presented to show the validity of the proposed results.

Application of a Zero-speed Fin Stabilizer for Roll Reduction of a Marine Robot near the Surface

A zero-speed fin stabilizer system was developed for rolling control of a marine robot.As a robot steering device near the sea surface with low speed,it will have rolling motion due to disturbance from waves.Based on the working principle of a zero-speed fin stabilizer and a marine robot’s dynamic properties,a roll damping controller was designed with a master-slave structure.It was composed of a sliding mode controller and an output tracking controller that calculates the desired righting moment and drives the zero-speed fin stabilizer.The methods of input-output linearization and model reference were used to realize the tracking control.Simulations were presented to demonstrate the validity of the control law proposed.

Cutting CO_(2)emissions through demand side regulation:Implications from multi-regional input-output linear programming model

This study combines multi-regional inputoutput(MRIO)model with linear programming(LP)model to explore economic structure adjustment strategies for the reduction of carbon dioxide(CO_(2))emissions.A particular feature of this study is the identification of the optimal regulation sequence of final products in various regions to reduce CO_(2)emissions with the minimum loss in gross domestic product(GDP).By using China's MRIO tables 2017 with 28 regions and 42 economic sectors,results show that reduction in final demand leads to simultaneous reductions in GDP and CO_(2)emissions.Nevertheless,certain demand side regulation strategy can be adopted to lower CO_(2)emissions at the smallest loss of economic growth.Several key final products,such as metallurgy,nonmetal,metal,and chemical products,should first be regulated to reduce CO_(2)emissions at the minimum loss in GDP.Most of these key products concentrate in the coastal developed regions in China.The proposed MRIO-LP model considers the inter-relationship among various sectors and regions,and can aid policy makers in designing effective policy for industrial structure adjustment at the regional level to achieve the national environmental and economic targets.

Robust linear optimization under matrix completion

Linear programming models have been widely used in input-output analysis for analyzing the interdependence of industries in economics and in environmental science.In these applications,some of the entries of the coefficient matrix cannot be measured physically or there exists sampling errors.However,the coefficient matrix can often be low-rank.We characterize the robust counterpart of these types of linear programming problems with uncertainty set described by the nuclear norm.Simulations for the input-output analysis show that the new paradigm can be helpful.

The Dynamics Characteristics of Flexible Spacecraft and Its Closed-Loop Stability with Passive Control

Passive control is the most popular methodology for flexible spacecraft while it remains an open problem whether the closed-loop performance can be achieved only with passive control subject to the coupling modes of rigid and flexibility.Also,the closed-loop performance of passive PD control based on the dynamics of the Euler angle parameterization of spacecraft,which has been widely used in practice,is yet to be addressed.Towards these challenges,by introducing the input-output exact linearization theory and Lyapunov theory,the authors show that the closed-loop performance for flexible spacecraft with rigid and flexible modes can be achieved by adjusting the parameters of the passive controllers sufficiently large.This is done by firstly transforming the flexible spacecraft dynamics into an exact feedback linearization standard form,and then analyzing the closed-loop performance of flexible spacecraft.

Industrial structure optimization in central China under the energy constraint

Optimizing industrial structure is an important research object of human-economic geography, and it is also the object of government departments to strengthen macro-control. This has become even greater problem that China has entered the "new normal" in recent years. The study uses a multi-regional input-output model, with linear programming to build an optimal model of industrial structure as well as a model of optimization degree under the energy constraint. The results of the study revealed that:(1) the degree of optimization of industrial structure in Anhui Province is optimal(0.763), while that of Shanxi Province is the lowest(0.662);(2) the degree of optimization of industrial structure is negatively related to energy consumption per unit output value and the proportion of heavy industry; and(3) overall, central China should maintain or moderately increase the proportions of resource-based industry, greatly increase the proportions of manufacturing, including transport and telecommunications equipment, computers and other electronic equipment, and moderately reduce the proportions of smelting and pressing of metals and non-metal mineral products. In terms of service industries, the region should greatly increase the proportions of the production and supply of natural gas and tap water, moderately reduce or maintain the proportions of transport and storage as well as tourism, and maintain or moderately reduce the proportions of wholesale trade, retail trade and catering services.