The traditional identification methods of industrial robots are based on Inverse Dynamic Identification Model (IDIM). Based on the model, input torque, motor-side and link-side motion data are necessary when joint flexibilities are considered. However, it is often unavailable or expensive to general robots which are not equipped with link-side sensors. To solve the problem, a novel dynamic parameter identification method, which only employ input torque and motor-side motion data, is proposed in this report. Based on motor-side dynamics, link-side dynamics are modified as high-order nonlinear functions of input torque and motor-side motion. Then, through different trajectory-load groups and high-order observers, the nonlinear equations can be solved, and dynamic parameters can be estimated with short operation time. The selection rules of the trajectory-load groups are then discussed based on simulation results, so as to promote estimation results. Finally, experiments are conducted to verify the proposed method and exhibit the selection rules of observer gains. As shown in the report, except viscous friction parameters, identification difference between the IDM-based methods and the proposed one is less than 9%.

A novel second-order sliding-mode-based impact angle and autopilot lag guidance law for engaging manoeuvering targets with unknown acceleration is presented in this study. A backstepping technique is applied to the design of the sliding surface. The proposed guidance law is based on a new sliding surface. It exhibits the advantage of ensuring that the sliding surface and its derivative will converge to zero in finite time while guaranteeing that the sliding surface will not cross zero until the ultimate time. The method effectively eliminates the undesired chattering of the sliding surface. To compensate for the uncertainty caused by target manoeuvering, a new observer is developed to estimate target manoeuvering. The convergence of the system is proven through a Lyapunov function and finite time convergence theory. Lastly, mathematical simulations results show that the proposed guidance law can achieve precise interception with a wide range of impact angles, thereby verifying the effectiveness of the guidance law.

It is known that pigs can acquire flavour preferences by brief social interactions with conspecifics that previously consumed a flavoured solid feed. However, there is no information about whether a flavoured solution could support flavour preferences through social transmission. Ninety-six pigs (49 days old) were housed in 12 pens (8 pigs/pen). Four animals per pen were randomly selected to act as observers and four as demonstrators. Demonstrator animals were temporarily moved to an empty pen where a protein solution was offered (porcine digestive peptides (PDPs), 4% weight/volume) with the addition of 0.075% aniseed (six pens) or garlic (six pens) powdered artificial flavours for 30 min. Afterwards, demonstrators were returned to interact with observer animals for 30 min. A choice test (30 min) between aniseed and garlic PDP was performed for each observer group after the interaction. Observers showed a higher intake of solutions previously consumed by their demonstrator conspecifics (648 v. 468 ml; SEM 61.36, P < 0.05). As with flavoured solid feeds, protein solutions containing artificial flavours can create preferences in pigs for those flavours through social transmission from conspecifics.

Body condition scoring is a common tool to assess the subcutaneous fat reserves of dairy cows. Because of its subjectivity, which causes limits in repeatability, it is often discussed controversially. Aim of the current study was to evaluate the impact of considering the cows overall appearance on the scoring process and on the validity of the results. Therefore, two different methods to reveal body condition scores (BCS), ‘independent BCS’ (iBCS) and ‘dependent BCS’ (dBCS), were used to assess 1111 Swiss Brown Cattle. The iBCS and the dBCS systems were both working with the same flowchart with a decision tree structure for visual and palpatory assessment using a scale from 2 to 5 with increment units of 0.25. The iBCS was created strictly complying with the defined frames of the decision tree structure. The system was chosen due to its formularized approach to reduce the influence of subjective impressions. By contrast, the dBCS system, which was in line with common practice, had a more open approach, where – besides the decision tree – the overall impression of the cow’s physical appearance was taken into account for generating the final score. Ultrasound measurement of the back fat thickness (BFT) was applied as a validation method. The dBCS turned out to be the better predictor of BFT, explaining 67.3% of the variance. The iBCS was only able to explain 47.3% of the BFT variance. Within the whole data set, only 31.3% of the animals received identical dBCS and iBCS. The pin bone region caused the most deviations between dBCS and iBCS, but also assessing the pelvis line, the hook bones and the ligaments led to divergences in around 20% of the scored animals. The study showed that during the assessment of body condition a strict adherence to a decision tree is a possible source of inexact classifications. Some body regions, especially the pin bones, proved to be particularly challenging for scoring due to difficulties in assessing them. All the more, the inclusion of the overall appearance of the cow into the assessment process counteracted these errors and led to a fair predictability of BFT with the flowchart-based BCS. This might be particularly important, if different cattle types and breeds are assessed.

The stabilization with time delay in observation or control represents difficult mathematical challenges in the control of distributed parameter systems. It is well-known that the stability of closed-loop system achieved by some stabilizing output feedback laws may be destroyed by whatever small time delay there exists in observation. In this paper, we are concerned with a particularly interesting case: Boundary output feedback stabilization of a one-dimensional wave equation system for which the boundary observation suffers from an arbitrary long time delay. We use the observer and predictor to solve the problem: The state is estimated in the time span where the observation is available; and the state is predicted in the time interval where the observation is not available. It is shown that the estimator/predictor based state feedback law stabilizes the delay system asymptotically or exponentially, respectively, relying on the initial data being non-smooth or smooth. Numerical simulations are presented to illustrate the effect of the stabilizing controller.

In this work, we propose an output feedback sliding mode control (SMC) method for trajectory tracking of robotic manipulators. The design process has two steps. First, we design a stable SMC controller by assuming that all state variables are available. Then, an output feedback version of this SMC design is presented, which incorporates a model-free linear observer to estimate unknown velocity signals. We then show that the tracking performance under the output feedback design can asymptotically converge to the performance achieved under state-feedback-based SMC design. A detailed stability analysis is given, which shows semi-global uniform ultimate boundedness property of all the closed-loop signals. The proposed method is implemented and evaluated on a robotic system to illustrate the effectiveness of the theoretical development.

Maximum load carrying capacity (MLCC) of flexible robot manipulators is computed based on closed-loop approach. In open-loop approach, controller is not considered, so the end effector deviation from the predefined path is significant and the accuracy constraint restrains the maximum payload before actuators go into saturation mode. In order to improve the MLCC, a method based on closed-loop strategy is presented. Since in this case the accuracy is improved the actuators constraint is not a major concern and full power of actuators can be used. Since controller can play an important role in improving the maximum payload, a sliding mode based partial feedback linearization controller is designed. Furthermore, a fuzzy variable layer is used in sliding mode design to boost the performance of the controller. However, the control strategy required measurements of elastic variables velocity that are not conveniently measurable. So a nonlinear observer is designed to estimate these variables. Stability analysis of the proposed controller and state observer are performed on the basis of Lyapunov's direct method. In order to verify the effectiveness of the presented method, simulation is done for a two-link flexible manipulator. The obtained maximum payload in open-loop and closed-loop cases is compared and the superiority of the method is illustrated and the results are discussed.

Based on the author's knowledge the paper gives a brief account of some of the scientific achievements of robotics that were of crucial importance to its development.

In a rough chronological order these are: zero-moment concept and semi-inverse method; recursive formulation of robot dynamics; computer-aided derivation of robot dynamics in symbolic form; dynamic approach to generation of trajectories of robotic manipulators; centralized feedforward control in robotics; robot dynamic control; decentralized control and observer applied to strongly coupled active mechanisms; force feedback in dynamic control of robots; decentralized control stability tests for robotic mechanisms; underactuated robotic systems; practical stability tests in robotics; unified approach to control laws synthesis for robot interacting with dynamic environment; modeling and control of multi-arm cooperating robots interacting with environment; connectionist algorithms for advanced learning control of robots interacting with dynamic environment; fuzzy logic robot control with model-based dynamic compensation, and internal redundancy – a new way to improve robot dynamic performance.