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In this paper, we presents a new nonlinear iterative learning control law for a class of nonlinear systems, denoted NP-D-INP-D, which is composed by limiting the action of error in PID learning law, that is, use a bounded nonlinear function of error instead of error, and adding a differential feedback in the integrator of PID learning law to inject the suited damping. By using Bellman-Gronwall lemma,...
This paper deals with the problem of optimizing a fuzzy self-tuning PID controller for robot manipulators. Fuzzy PID controllers have been developed and applied in many fields in the last fifteen years. However, there is no systematic method to design Membership Functions (MFs) for these controllers. We propose a simple method based on Genetic Algorithms (GA) to find optimal input and output MFs of...
In this paper, we presents a new class of iterative learning control law for a class of nonlinear systems, denoted PD-IPD, which is composed by adding a derivative term in the integrator of PID learning control law. By using Bellman-Gronwall lemma, the simple explicit conditions on the learning gains to ensure convergence are provided in the sense of Lambda norm. An attractive feature of PD-IPD learning...
Position control of expedition robots are considered. The robots are controlled to follow pre-determined paths via fixed way-points. The speed and heading are controlled to follow reference values calculated from the next way point and current position. Hybrid control is used for speed loop and heading loop, respectively. Depending on the parameter change of speed and heading model due to unexpected...
This paper presents a task-space saturated-proportional, integral and differential (SP-ID) regulation approach for robot manipulators with uncertain kinematics and actuator model. The proposed approach is computationally efficient and easy to implement due to its simple structure. It's interesting to observe that in this paper the simple PID type controller is shown not only capable of compensating...
In a certain robot control benchmark it is known that certain types of disturbances occur. This paper presents a classifier that gives a fuzzy estimate of the disturbance that is currently affecting the process. The classifier uses the discrete wavelet transform to extract features from the measurement signal. Based on the features, a fuzzy inference system gives an estimate of the proportion of different...
In this paper, model-based adaptive control is presented for a differentially driven wheeled mobile robot. The controller takes into account of robot dynamics and the coupling between the motions of the two differential wheels. It can achieve better speed tracking than the commonly used model-free PID controller. Simulation studies are carried out to verify the effectiveness of the proposed approaches.
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