H.K. Lam
King's College London, Informatics, Faculty Member
- Fuzzy Control, Fuzzy-Model-Based Control, Stability Analysis, Nonlinear Systems, Intelligent Control, Nonlinear Control, and 11 moreController Design, Fuzzy Logic Control, Lyapunov Stability Theory, Neural Networks, Artificial Neural Networks, Computational Intelligence, Control and Synchronization of Chaotic/Hyperchaotic Systems, Classification (Machine Learning), Pattern Recognition, Genetic Algorithms, and Meta-Heuristics (Tabu Search, Genetic Algorithms, Simulated Annealing, Ant-Colony, Particle Swarm Optimization)edit
Abstract This study investigates the systems stability of fuzzy-model-based (FMB) control systems. Based on the TS fuzzy model representing the non-linear system, a fuzzy controller using grid-point (GP) technique is proposed to close the... more
Abstract This study investigates the systems stability of fuzzy-model-based (FMB) control systems. Based on the TS fuzzy model representing the non-linear system, a fuzzy controller using grid-point (GP) technique is proposed to close the feedback loop. A GP is defined as the sub-operating domain of the non-linear system. For each GP, a corresponding GP fuzzy controller is employed to control the system. As the non-linearity in each GP is lower compared to that of the full operating domain, it is in favour of yielding relaxed stability ...
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This paper investigates the stability of polynomial-fuzzy-model-based (PFMB) control system, which is formed by a polynomial fuzzy model and a polynomial fuzzy controller connected in a closed loop. To enhance the design flexibility, the... more
This paper investigates the stability of polynomial-fuzzy-model-based (PFMB) control system, which is formed by a polynomial fuzzy model and a polynomial fuzzy controller connected in a closed loop. To enhance the design flexibility, the number of rules and the shape of premise membership functions of the polynomial fuzzy controller are considered to be chosen freely and are different from those of the polynomial fuzzy model, however, which make the stability analysis more difficult and potentially lead to conservative stability analysis result. A sum-of-squares (SOS)-based stability analysis approach using the Lyapunov stability theory is proposed to investigate the stability of the PFMB control systems and synthesize the polynomial fuzzy controller. To facilitate the stability analysis and relax the stability analysis result, the property of the membership functions and the boundary information of the membership grades and premise variables are taken into account in the stability analysis and incorporated into the SOS-based stability conditions. A simulation example is given to illustrate the effectiveness of the proposed approach.
This paper focuses on designing interval type-2 (IT2) control for nonlinear systems subject to parameter uncertainties. To facilitate the stability analysis and control synthesis, an IT2 Takagi-Sugeno (T-S) fuzzy model is employed to... more
This paper focuses on designing interval type-2 (IT2) control for nonlinear systems subject to parameter uncertainties. To facilitate the stability analysis and control synthesis, an IT2 Takagi-Sugeno (T-S) fuzzy model is employed to represent the dynamics of nonlinear systems of which the parameter uncertainties are captured by IT2 membership functions characterized by the lower and upper membership functions. A novel IT2 fuzzy controller is proposed to perform the control process, where the membership functions and number of rules can be freely chosen and different from those of the IT2 T-S fuzzy model. Consequently, the IT2 fuzzy-model-based (FMB) control system is with imperfectly matched membership functions, which hinders the stability analysis. To relax the stability analysis for this class of IT2 FMB control systems, the information of footprint of uncertainties and the lower and upper membership functions are taken into account for the stability analysis. Based on the Lyapunov stability theory, some stability conditions in terms of linear matrix inequalities are obtained to determine the system stability and achieve the control design. Finally, simulation and experimental examples are provided to demonstrate the effectiveness and the merit of the proposed approach.
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This paper presents the graffiti interpretation of one-stroke handwritten digits (0 to 9) and commands (backspace, carriage return and space) using support vector machines (SVMs). A number of SVM-based graffiti interpreters are proposed... more
This paper presents the graffiti interpretation of one-stroke handwritten digits (0 to 9) and commands (backspace, carriage return and space) using support vector machines (SVMs). A number of SVM-based graffiti interpreters are proposed for the recognition of graffiti. The performance of the proposed SVM-based graffiti interpreters subject to various kernel functions and parameters are investigated. Simulation and experimental results are presented to show the applicability and the merits of various graffiti interpreters.
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Research Interests: Algorithms, Computer Graphics, Artificial Intelligence, Publishing, Electronic publishing, and 15 moreGenetic Algorithms, Reading, Neural Networks, Neural Network, Multidisciplinary, Genetic Algorithm, Handwriting, Books, Computer User Interface Design, Information Storage and Retrieval, Image Enhancement, Reproducibility of Results, Word Processing, Sensitivity and Specificity, and Automatic data processing
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This paper presents the stability analysis and control synthesis for a sampled-data control system which consists of a nonlinear plant and an output-feedback sampled-data polynomial controller connected in a closed loop. The... more
This paper presents the stability analysis and control synthesis for a sampled-data control system which consists of a nonlinear plant and an output-feedback sampled-data polynomial controller connected in a closed loop. The output-feedback sampled-data polynomial controller, which can be implemented by a microcontroller or a digital computer, is proposed to stabilize the nonlinear plant. Based on the Lyapunov stability theory, stability conditions in terms of sum of squares are obtained to guarantee the stability and to aid the design of a polynomial controller. A simulation example is given to demonstrate the effectiveness of the proposed control approach.
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This paper proposes a linear sampled-data controller for the stabilization of chaotic system. The system stabilization and performance issues will be investigated. Stability conditions will be derived based on the Lyapunov approach. The... more
This paper proposes a linear sampled-data controller for the stabilization of chaotic system. The system stabilization and performance issues will be investigated. Stability conditions will be derived based on the Lyapunov approach. The findings of the maximum sampling period and the feedback gain of controller, and the optimization of system performance will be formulated as a generalized eigenvalue minimization problem. Based on the analysis result, a stable linear sampled-data controller can be realized systematically to stabilize a chaotic ...
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This Letter presents the chaos synchronization of two discrete-time generalized Hénon map, namely the drive and response systems. A polynomial controller is proposed to drive the system states of the response system to follow those of the... more
This Letter presents the chaos synchronization of two discrete-time generalized Hénon map, namely the drive and response systems. A polynomial controller is proposed to drive the system states of the response system to follow those of the drive system. The system stability of the error system formed by the drive and response systems and the synthesis of the polynomial controller are investigated using the sum-of-squares (SOS) technique. Based on the Lyapunov stability theory, stability conditions in terms of SOS are derived to guarantee the system stability and facilitate the controller synthesis. By satisfying the SOS-based stability conditions, chaotic synchronization is achieved. The solution of the SOS-based stability conditions can be found numerically using the third-party Matlab toolbox SOSTOOLS. A simulation example is given to illustrate the merits of the proposed polynomial control approach.
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Abstract This paper presents the stability analysis, synthesis, and performance optimization of a radial-basis-function neural-network based control system. Global stability conditions will be derived in terms of matrix measure. Based on... more
Abstract This paper presents the stability analysis, synthesis, and performance optimization of a radial-basis-function neural-network based control system. Global stability conditions will be derived in terms of matrix measure. Based on the derived stability conditions, connection weights of the radial-basis-function neural-network based controller can be optimized by genetic algorithm (GA) subject to the system stability. Furthermore, the system performance will also be optimized by the GA. An application example on stabilizing an ...
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This paper describes the design and development of a path planning method for Micro Robot Soccer Tournament (MIROSOT). Every object in the stadium is given a working layer which is decomposed into a fixed number of small areas. We propose... more
This paper describes the design and development of a path planning method for Micro Robot Soccer Tournament (MIROSOT). Every object in the stadium is given a working layer which is decomposed into a fixed number of small areas. We propose to assign values to different small areas of the layer according to the object's movement. The final path is obtained by combining the small areas of the layers and getting the path with the smallest values. Since the host computer uses only a simple equation to calculate the value of each small area, this algorithm requires only a low computing power, and the speed of path generation is very fast. A simulation program was developed to test the algorithm's performance
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This paper describes the design and development of a path planning method for Micro Robot Soccer Tournament (MIROSOT). Every object in the stadium is given a working layer which is decomposed into a fixed number of small areas. We propose... more
This paper describes the design and development of a path planning method for Micro Robot Soccer Tournament (MIROSOT). Every object in the stadium is given a working layer which is decomposed into a fixed number of small areas. We propose to assign values to different small areas of the layer according to the object's movement. The final path is obtained by combining the small areas of the layers and getting the path with the smallest values. Since the host computer uses only a simple equation to calculate the value of each small area, this algorithm requires only a low computing power, and the speed of path generation is very fast. A simulation program was developed to test the algorithm's performance
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Abstract Presents a decision maker, which will select the appropriate tactics and actions for soccer robots according to the condition of a tournament. The selected tactic will be employed to assign each home robot an action to play the... more
Abstract Presents a decision maker, which will select the appropriate tactics and actions for soccer robots according to the condition of a tournament. The selected tactic will be employed to assign each home robot an action to play the game. The decision maker consists of a tactic database, an action database, a tactic selection algorithm, a tactic selector and an action selector. Simulation results are given to show the merits of the proposed algorithm
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This paper investigates the synchronization of chaotic systems using an output feedback polynomial controller. As only output system states are considered, it makes the controller design and system analysis more challenging compared to... more
This paper investigates the synchronization of chaotic systems using an output feedback polynomial controller. As only output system states are considered, it makes the controller design and system analysis more challenging compared to the full-state feedback control schemes. To study the system stability and synthesize the output feedback polynomial controller, Lyapunov stability theory is employed. Sufficient stability conditions are derived in terms of sum of squares (SOS) conditions to guarantee the system stability and aid the ...
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Abstract This paper presents stability analysis of polynomial fuzzy-model-based (FMB) control systems using the sum-of-squares (SOS) approach. Recently, stability analysis of the polynomial fuzzy-control systems, which is a generalized... more
Abstract This paper presents stability analysis of polynomial fuzzy-model-based (FMB) control systems using the sum-of-squares (SOS) approach. Recently, stability analysis of the polynomial fuzzy-control systems, which is a generalized form of the well-known Takagi-Sugeno (TS) FMB control systems, has been reported in the form of SOS-based stability conditions. Lack of information on the relations between membership functions and premise variables, in the existing stability analysis approaches, causes conservatism of their ...
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This paper presents the synchronization of chaotic systems. A feed-forward neural network will be employed to form the proposed neural-network-based controller to perform chaotic synchronization. Stability conditions will be derived to... more
This paper presents the synchronization of chaotic systems. A feed-forward neural network will be employed to form the proposed neural-network-based controller to perform chaotic synchronization. Stability conditions will be derived to guarantee the system stability. The system performance will be ensured and the parameters of the neural networks can be obtained by solving the solution to the generalized eigenvalue minimization problem. A simulation example will be given to illustrate the effectiveness of the proposed approach.
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Abstract This study presents the synchronisation of two chaotic systems, namely drive and response chaotic systems, using polynomial controllers. Both output and full state-feedback polynomial controllers are proposed, respectively, to... more
Abstract This study presents the synchronisation of two chaotic systems, namely drive and response chaotic systems, using polynomial controllers. Both output and full state-feedback polynomial controllers are proposed, respectively, to drive the system states of the response system to approach those of the drive one. The system stability of the overall system is investigated by the Lyapunov stability theory. Stability conditions in terms of sum of squares (SOS) are derived to aid the design of the feedback gains of the polynomial controllers. By ...
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Research Interests: Algorithms, Genetic Algorithms, Nonlinear dynamics, Stability, Neural Network, and 14 moreMultidisciplinary, Genetic Algorithm, Control system, Linear Matrix Inequalities, Computer Simulation, Stability Analysis, Feedback, Sample Size, Feedforward Neural Network, Theoretical Models, Nonlinear system, Continuous Time Systems, Sampled-data Control, and Linear Matrix Inequality
This paper presents a neural-tuned neural network (NTNN), which is trained by an improved genetic algorithm (GA). The NTNN consists of a common neural network and a modified neural network (MNN). In the MNN, a neuron model with two... more
This paper presents a neural-tuned neural network (NTNN), which is trained by an improved genetic algorithm (GA). The NTNN consists of a common neural network and a modified neural network (MNN). In the MNN, a neuron model with two activation functions is introduced. An improved GA is proposed to train the parameters of the proposed network. A set of improved genetic operations are presented, which show superior performance over the traditional GA. The proposed network structure can increase the search space of the ...
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This paper presents a neural network model with a variable structure, which is trained by an improved genetic algorithm (GA). The proposed variable-structure neural network (VSNN) consists of a neural network with link switches (NNLS) and... more
This paper presents a neural network model with a variable structure, which is trained by an improved genetic algorithm (GA). The proposed variable-structure neural network (VSNN) consists of a neural network with link switches (NNLS) and a network switch controller (NSC). In the NNLS, switches in its links between the hidden and output layers are introduced. By introducing the NSC to control the switches in the NNLS, the proposed neural network can model different input patterns with variable network structures. The proposed network gives better results and increased learning ability than conventional feed-forward neural networks. An industrial application on short-term load forecasting in Hong Kong is given to illustrate the merits of the proposed network.
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Abstract This paper presents an algorithm of playing game tic-tac-toe. This algorithm is learned by a modified neural network (NN), which is trained by an improved genetic algorithm (GA). In the proposed NN, the neuron has two activation... more
Abstract This paper presents an algorithm of playing game tic-tac-toe. This algorithm is learned by a modified neural network (NN), which is trained by an improved genetic algorithm (GA). In the proposed NN, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer that enhances the learning ability of the network. It will be shown that the proposed NN and GA provide a better performance than the traditional approach.
This paper presents the estimation of the transmission gain for the AC power line data network in an intelligent home. The estimated gain ensures the transmission reliability and efficiency. A neural network with link switches is proposed... more
This paper presents the estimation of the transmission gain for the AC power line data network in an intelligent home. The estimated gain ensures the transmission reliability and efficiency. A neural network with link switches is proposed to perform the estimation. Genetic algorithm with arithmetic crossover and nonuniform mutation is employed to tune the parameters and the structure of the proposed neural network. An application example will be given.
The paper presents an electric load balancing system for domestic use. An electric load forecasting system, which is realized by a genetic algorithm-based modified neural network, is employed. On forecasting the home power consumption... more
The paper presents an electric load balancing system for domestic use. An electric load forecasting system, which is realized by a genetic algorithm-based modified neural network, is employed. On forecasting the home power consumption profile, the load balancing system can adjust the amount of energy stored in battery accordingly, preventing it from reaching certain practical limits. A steady consumption from the AC mains can then be obtained which will benefit both the users and the utility company. An example will be given to illustrate ...
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This paper studies the stability issue of the average queue length of a Transmission Control Protocol (TCP) model when interacting with Random Early Detection (RED). The model used for the study has shown period doubling bifurcation (PDB)... more
This paper studies the stability issue of the average queue length of a Transmission Control Protocol (TCP) model when interacting with Random Early Detection (RED). The model used for the study has shown period doubling bifurcation (PDB) and border collision bifurcation (BCB) in the average queue size at certain values of parameters when original RED is deployed. In this paper, we adopt a gentle version of RED and a newly derived RED algorithm into the model to study the improvement in stability of average queue size of the ...
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Relaxed LMI-based stability conditions for fuzzy model-based (FMB) control systems with imperfect premise matching are proposed. Information of membership functions containing relations between state variables and membership functions are... more
Relaxed LMI-based stability conditions for fuzzy model-based (FMB) control systems with imperfect premise matching are proposed. Information of membership functions containing relations between state variables and membership functions are taken into stability analysis. Firstly, based on the Lyapunov stability theorem, derivative of quadratic Lyapunov function containing product terms of fuzzy model and fuzzy controller's membership functions are derived. Then, the operating domain of membership functions is partitioned to sub-regions, such that each product term of fuzzy model and fuzzy controller membership functions is approximated properly with a polynomial of state variables. Next, in each sub-region LMI-based stability conditions containing the information of subsystems and approximated polynomials are derived. It is shown that the previous stability conditions can be as special cases of the proposed stability conditions. Finally, simulation example is given to illustrate the validity and effectiveness of the proposed approach.
Research Interests: Algorithms, Artificial Intelligence, Fuzzy Logic, Fuzzy set theory, Fuzzy Systems, and 18 moreStability, Multidisciplinary, Control Systems, Fuzzy Control, Control system, Linear Matrix Inequalities, Computer Simulation, Stability Analysis, Feedback, Shape, Membership Function, Fuzzy System, Lyapunov function, Numerical Stability, Polynomials, Asymptotic Stability, Approximation Method, and Linear Matrix Inequality
This paper presents the stability analysis of sampled-data output-feedback polynomial fuzzy-model-based control systems. A sampled-data output-feedback polynomial fuzzy controller is proposed to control the nonlinear plant represented by... more
This paper presents the stability analysis of sampled-data output-feedback polynomial fuzzy-model-based control systems. A sampled-data output-feedback polynomial fuzzy controller is proposed to control the nonlinear plant represented by the polynomial fuzzy model. The proposed sampled-data output-feedback polynomial fuzzy controller makes use of the system output for control. Furthermore, due to the sampling activity, the control signal will be kept constant during the sampling period which complicates the system dynamics and makes the stability analysis difficult. The system stability is investigated based on the Lyapunov stability theory using the sum-of-squares (SOS) approach. SOS-based stability conditions are derived to guarantee the system stability and aid the stable design of the sampled-data output-feedback polynomial fuzzy controller. With the third-party Matlab toolbox SOSTOOLS, the solution to the SOS-based stability conditions can be found numerically. A simulation example is given to demonstrate the merits of the proposed control approach.
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Abstract This paper presents the stability analysis of polynomial fuzzy-model-based (PFMB) control systems using the sum-of-squares (SOS) approach. The PFMB control system under consideration requires that the polynomial fuzzy model and... more
Abstract This paper presents the stability analysis of polynomial fuzzy-model-based (PFMB) control systems using the sum-of-squares (SOS) approach. The PFMB control system under consideration requires that the polynomial fuzzy model and polynomial fuzzy controller share neither the same premise membership functions nor the same number of fuzzy rules. This class of PFMB control systems offers a greater design flexibility to the polynomial fuzzy controller. However, due to the imperfectly matched membership functions, it usually ...