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This paper takes software method to compensate temperature against the drift problem of piezoresistive waist force sensor. The compensation algorithm is modeled through using the PLS method. And compensation module is designed based on multiple regression method. According to the simulation results, the system designed meet the basic phenomenon for drift correction. Finally, the actual data is used to validate this algorithm.

The main function of the wrist force sensor in robot remote operation is to realize the force feedback, one as a necessary part of the contact force of the process itself; another is the contact force as a robot gripper with respect to the environment the exact location of the information source, wrist force sensor provides information can reduce the robot to peripheral equipment precision requirement. Remote sensing operation environment, the manipulator and the environment from the direct effect of the information, the wrist force sensor detection, conversion, transmission to the master, for the establishment of virtual environment and the main basis and real-time interactive environment. The sensor circuit system design, designed the bridge circuit is applicable, overall on the measurement system is designed, and for sensor data acquisition software programming theory.

When the drive system of two-phase hybrid stepper motor adopts the traditional hysteresis loop control mode, it has good dynamic response performance, but also has some disadvantages such as big current ripple and big noise. In view of the above problems, the given current within one period of the winding is divided into ascending area, flat area and descending area, and the different demands for the rate of change of current in each area are analyzed in this paper. Compared with the traditional hysteresis loop, the three-state hysteresis loop has more switch combinations, which can meet the requirement of switching multiple current change rate in the driving system of two-phase hybrid stepping motor. This control algorithm based on three-state hysteresis loop presented in this paper can not only guarantee the dynamic response performance, but also greatly reduce the current ripple. The relationship between current ripple and terminal voltage, inductance and control frequency is derived in this paper. The hardware platform was set up with Cyclone IV FPGA of Altera company as the core processing chip, and the two-phase hybrid stepping motor of Oriental motor company model PK299DB was taken as the control object for experimental verification. Simulation and experiment verify the effectiveness of the algorithm.

In the actual system the law of changing with time of continuous signal can be completely described by the signal frequency spectrum. Only choose the reasonable sampling frequency and sampling time zone width, signal spectrum can approximate continuous signal actual spectrum. Because of the frequency leakage and spectrum aliasing existence, the analysis result which has a minimum of spectrum component has the most close to the continuous signal spectrum. Through the particle swarm optimization algorithm is used to choose different sampling data amount, make sampling time length just be integer times of continuous signal sampling period (or approximate cycle), then it can completely eliminate (or partly eliminate) spectrum leakage of sampling data, thus make sampling data spectrum and the sampling continuous signal spectrum completely (or as) consistent, realize spectrum of band-limited discrete spectrum continuous signal accurate recognition.

This paper is focused on stability analysis of net-worked control systems with randomly varying delay and missing measurements. It is assumed that the parameter uncertainties are norm-bounded and the delay is random. Missing measurements are described by a binary switching sequence that obeys the Bernoulli distribution. By employing reciprocally convex approach proposed recently, together with delay de-composition approach, a delay-distribution-dependent stability criterion is derived such that the system is robustly asymptotically stable for all admissible uncertainties. Finally, a numerical example is given to illustrate the effectiveness of the proposed method in this paper.

In order to make robust decisions under uncertainty, the stochastic optimization method is proposed to effectively realize the optimal control of alumina blending process. Firstly, the multi-objective stochastic optimization model is built to describe the quality requirements of multiple indices and to incorporate uncertainty into the optimization problem. Then, Hammersley sequence sampling(HSS)technique is used to generate the samples of the stochastic variables and the equivalent deterministic optimization model is obtained. Finally, the multi-objective hierarchical expert reasoning strategy based on the empirical knowledge accumulated in long-term production is proposed to realize the optimal control of blending process with uncertainty. The results of industrial application shows that the proposed method can effectively control the quality indices under parametric uncertainty. It provides a good optimization mode for other blending processes of nonferrous metal production with uncertainty.

The delay-dependent robust stability for neutral systems with time-varying delay is discussed. By using the Lyapunov-Krasovskii functional method and following the free weighing matrix lines, a new delay-dependent stability sufficient condition is obtained by introducing some free matrices in the derivative of the Lyapunov-Krasovskii functional. The numerical examples show that the results of this paper have advantages over existing ones.

This paper is concerned with the problem of Hinfin filtering for a class of linear systems with Markovian jump parameters and mode-dependent time-varying delays. The Lyapunov-Krasovskii method is used to derive a new delay-dependent Bounded Real Lemma (BRL) incorporating with an integral inequality, which guarantees that the filtering error system is not only exponentially stable in the mean square sense and with a guaranteed level of Hinfin noise attenuation as well. Then, some delay-dependent sufficient conditions for the existence of a suitable Markovian jump linear filter are established based on a set of strict linear matrix inequalities (LMIs). Some examples are given to show the effectiveness of the proposed method in this paper.

This paper is concerned with the delay-dependent stability for linear systems with time delays. By decomposing the delay interval into three equidistance subintervals, on which different Lyapunov functionals are defined, a new Lyapunov-Krasvskii functional is then constructed. With its help, a series of new delay dependent stability criteria are established for both constant and time-varying delays. Some numerical examples are finally given to show that the obtained results are less conservative than those in the literature.

This paper is concerned with the problem of delay-dependent non-fragile Robust H-infinite control for uncertain systems. Based on an integral inequality method, a new delay-dependent condition, which can ensure that the closed-loop system is internally stable with a given H-infinite disturbance attenuation level via a non-fragile controller, is obtained by using the Lyapunov-Krasovskii stability theory. Then, the design of non-fragile H-infinite controller is proposed. No any parameter needs to be tuned. It can be easily solved in terms of linear matrix inequalities (LMI) in Matlab Toolbox. Finally, a numerical simulation is given to show the validity of this approach.